The repo you mentioned is about fine-tuning the Llama model for production use cases. It provides examples and documentation to make the repo approachable for users who want to do their own fine-tuning. If you have any questions or encounter any issues while using the repo, the author is available to help. Additionally, there are other repositories mentioned that provide guidance on fine-tuning Llama models to speak like Homer Simpson and provide instructions on running Llama models locally. These repositories offer step-by-step instructions and code snippets to help you get started. References: 1. [Fine-tuning Qlora for Production Use Cases](https://www.reddit.com/r/LocalLLaMA/comments/1521gni/finetuning_qloras_for_production_use_cases/) 2. [Fine-tune Llama to Speak like Homer Simpson](https://replicate.com/blog/fine-tune-llama-to-speak-like-homer-simpson) 3. [How to Run LLMs Locally](https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx) 4. [Yet Another Llama2 Finetune](https://www.reddit.com/r/LocalLLaMA/comments/15azzgl/yet_another_llama2_finetune/) 5. [Llama C++ Repository](https://wandb.ai/capecape/llamac/reports/Training-Tiny-Llamas-for-Fun-and-Science--Vmlldzo1MDM2MDg0)
[Lecture 9 - PDF Transcript.pdf,https://utfs.io/f/9889e734-0586-403f-a10a-a313412c9de8-t2w2m8.pdf] (0) MachineLearning-Lecture09Instructor (Andrew Ng): All right, good morning Just one quick announcement, firstthings for all of your project proposals, I’ve read through all of them and they all lookfine There is one or two that I was trying to email back comments on that had slightlyquestionable aspects, but if you don’t hear by me from today you can safely assume thatyour project proposal is fine and you should just go ahead and start working on yourproposals You should just go ahead and start working on your project [Lecture 1 - PDF Transcript.pdf,https://utfs.io/f/b0e14d33-81c7-4db8-9202-c7b9145557eb-ixpqa0.pdf] (41) And take a look, then come up with your ownideas But whatever you find cool and interesting, I hope you'll be able to make machinelearning a project out of it Yeah, question?Student : Are these group projects?Instructor (Andrew Ng): Oh, yes, thank you Student : So how many people can be in a group?Instructor (Andrew Ng): Right [Lecture 4 - PDF Transcript.pdf,https://utfs.io/f/bcd77ba6-7f7d-4c74-8b69-ddc738ae3d16-uj6fkr.pdf] (2) And so if youwant to hear about some of those ideas in topics like on natural [inaudible], computervision, neuroscience, robotics, control So [inaudible] ideas and a variety of topics atthese, so if you’re having trouble coming up with your own project idea, come to myoffice hours or to TA’s office hours to ask us for suggestions, to brainstorm ideas with us Also, in the previous class I mentioned that we’ll invite you to become [inaudible] with229, which I think is a fun and educational thing to do So later today, I’ll also emaileveryone registered in this class with some of the logistical details about applying to be[inaudible] [Lecture 20 - PDF Transcript.pdf,https://utfs.io/f/74912b87-b7d8-43c4-8226-8eaf51ff4727-zhor2v.pdf] (103) Based on the projects you’ve done, I hope that most of you will be able to imagineyourself going out after this class and applying these things to solve a variety ofproblems Hopefully, some of you will also imagine yourselves writing research papersafter this class, be it on a novel way to do machine learning, or on some way of applyingmachine learning to a problem that you care about In fact, looking at project milestones,I’m actually sure that a large fraction of the projects in this class will be publishable, so Ithink that’s great I guess many of you will also go industry, make new products, andmake lots of money using learning [Lecture 4 - PDF Transcript.pdf,https://utfs.io/f/bcd77ba6-7f7d-4c74-8b69-ddc738ae3d16-uj6fkr.pdf] (1) If you haven’tyet formed teams or started thinking about project ideas, please do so And later today, you’ll find on the course website a handout with the guidelines and someof the details on how to send me your proposals and so on If you’re not sure whether an idea you have for a project may be a appropriate, or you’resort of just fishing around for ideas or looking for ideas of projects to do, please, bestrongly encouraged to come to my office hours on Friday mornings, or go to any of theTA’s office hours to tell us about your project ideas, and we can help brainstorm withyou I also have a list of project ideas that I sort of coll [Lecture 1 - PDF Transcript.pdf,https://utfs.io/f/b0e14d33-81c7-4db8-9202-c7b9145557eb-ixpqa0.pdf] (54) So many students will try to build a cool machine learning application That's probablythe most common project Some students will try to improve state-of-the-art machinelearning Some of those projects are also very successful [Lecture 1 - PDF Transcript.pdf,https://utfs.io/f/b0e14d33-81c7-4db8-9202-c7b9145557eb-ixpqa0.pdf] (53) Yeah?Student : Looking at the end semester project, I mean, what exactly will you be testingover there? [Inaudible]?Instructor (Andrew Ng) : Of the project?Student : Yeah Instructor (Andrew Ng) : Yeah, let me answer that later In a couple of weeks, I shallgive out a handout with guidelines for the project But for now, we should think of thegoal as being to do a cool piece of machine learning work that will let you experience thejoys of machine learning firsthand and really try to think about doing a publishable pieceof work [Lecture 1 - PDF Transcript.pdf,https://utfs.io/f/b0e14d33-81c7-4db8-9202-c7b9145557eb-ixpqa0.pdf] (42) So projects can be done in groups of up to three people So as part of forming study groups, later today as you get to know your classmates, Idefinitely also encourage you to grab two other people and form a group of up to threepeople for your project, okay? And just start brainstorming ideas for now amongstyourselves You can also come and talk to me or the TAs if you want to brainstorm ideaswith us So one more organizational question [Lecture 8 - PDF Transcript.pdf,https://utfs.io/f/91e8b7c1-bbfd-45b9-b0b5-74463d9e7274-pgl9en.pdf] (0) MachineLearning-Lecture08Instructor (Andrew Ng):Okay If you haven’t given methe homework yet, you can just give it to me at the end of class And also just a quick reminder – I’ve actually seen project proposals start to trickle inalready, which is great As a reminder, project proposals are due this Friday, and if any ofyou want to meet and chat more about project ideas, I also have office hours immediatelyafter lecture today [Lecture 11 - PDF Transcript.pdf,https://utfs.io/f/1a51a1c5-33ce-4c5d-9c61-7613083118e8-wytzsl.pdf] (127) This was – this is a sort of cartoon that highly influenced my ownthinking It was based on a paper written by Christos Papadimitriou This is how progress– this is how developmental progress of research often happens Right? Let’s say youwant to build a mail delivery robot, so I’ve drawn a circle there that says mail deliveryrobot --- provide me a first baby project to help me build up a portfolio. Something that is like a low hanging fruit of a project
Collama is a collaborative research tool that allows users to upload documents, invite others to join, and ask questions about those documents to deepen their understanding. It provides a platform for collaborative learning, research, and knowledge sharing. To use Collama, you can start by uploading relevant documents or articles that you want to discuss or gain insights from. Next, you can invite other users to join your research group or collaborate with existing members. Once your group is set up, you can start asking questions about the uploaded documents, share your thoughts, and engage in discussions with other members. Collama provides a space for collaborative exploration and learning. Ask more: - What are the benefits of collaborating on research using Collama? - Can I upload different types of documents, such as PDFs or Word files? - How can I invite others to join my research group? References: 1. [karpathy/nanoGPT](https://github.com/karpathy/nanoGPT) 2. [Parameter-Efficient Fine-Tuning.pdf](https://utfs.io/f/27375dee-f868-49fb-9c05-f5e41cf59bca-su1eqj.pdf) 3. [HN-How to Finetune GPT-Like Large Language Models on a Custom Dataset _ Hacker News.pdf](https://utfs.io/f/dbd7687c-51b9-4736-b3c7-a28274ed4e68-7a1hwz.pdf) 4. [QLORA- Efficient Finetuning of Quantized LLMs.pdf](https://utfs.io/f/a84afab2-2877-4146-b3df-c776ef63e7d7-jv9sw0.pdf) 5. [wandb.ai/mostafaibrahim17/ml-articles/reports/Fine-Tuning-ChatGPT-for-Question-Answering-With-W-B--Vmlldzo1NTEzNjU2](https://wandb.ai/mostafaibrahim17/ml-articles/reports/Fine-Tuning-ChatGPT-for-Question-Answering-With-W-B--Vmlldzo1NTEzNjU2) 6. [reddit.com/r/LocalLLaMA](https://www.reddit.com/r/LocalLLaMA/)
[https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (20) wandb: WARNING Source type is set to 'repo' but some required information is missing from the environment A job will not be created from this run See https://docs ai/guides/launch/create-job View run mild-surf-1 at: https://wandb [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (20) wandb: WARNING Source type is set to 'repo' but some required information is missing from the environment A job will not be created from this run See https://docs ai/guides/launch/create-job View run mild-surf-1 at: https://wandb [https://wandb.ai/ayush-thakur/llama-index-report/reports/Building-Advanced-Query-Engine-and-Evaluation-with-LlamaIndex-and-W-B--Vmlldzo0OTIzMjMy,https://wandb.ai/ayush-thakur/llama-index-report/reports/Building-Advanced-Query-Engine-and-Evaluation-with-LlamaIndex-and-W-B--Vmlldzo0OTIzMjMy] (12) init args wandb_args = {"project":"llama-index-report"} wandb_callback = WandbCallbackHandler(run_args=wandb_args) # pass wandb_callback to the service context callback_manager = CallbackManager([wandb_callback]) service_context = ServiceContext from_defaults(callback_manager=callback_manager) # Chunking and Embedding of the chunks index = VectorStoreIndex from_documents(documents, service_context=service_context) # Retrieval, node poseprocessing, response synthesis [https://wandb.ai/vincenttu/finetuning_mistral7b/reports/Fine-tuning-Mistral-7B-with-W-B--Vmlldzo1NTc3MjMy,https://wandb.ai/vincenttu/finetuning_mistral7b/reports/Fine-tuning-Mistral-7B-with-W-B--Vmlldzo1NTc3MjMy] (58) import wandb run = wandb init(project=wandb_project_name) # MAKE SURE TO PASS IN YOUR PROJECT NAME! artifact = run use_artifact('vincenttu/finetuning_mistral7b/model-t6rw0dav:v0', type='model') artifact_dir = artifact download() run [https://wandb.ai/vincenttu/finetuning_mistral7b/reports/Fine-tuning-Mistral-7B-with-W-B--Vmlldzo1NTc3MjMy,https://wandb.ai/vincenttu/finetuning_mistral7b/reports/Fine-tuning-Mistral-7B-with-W-B--Vmlldzo1NTc3MjMy] (45) More dynamic, low-level grouping notes="Logging preprocessed subset of Puffin dataset " # Description about the run ) # Check out the other parameters in the `wandb [https://github.com/OpenAccess-AI-Collective/axolotl,https://github.com/OpenAccess-AI-Collective/axolotl] (2) gitignore ignore wandb to resolve isort headaches (#619) cfg ignore wandb to resolve isort headaches (#619) ini Support Sample packing for phi arch (#586) pre-commit-config [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (19) Use [1m`wandb login --relogin`[0m to force relogin Tracking run with wandb version 0 9 Run data is saved locally in /Users/tcapelle/work/examples/colabs/openai/wandb/run-20230830_113853-ivu21mjl Syncing run mild-surf-1 to Weights & Biases (docs) View project at https://wandb ai/capecape/OpenAI-Fine-Tune View run at https://wandb ai/capecape/OpenAI-Fine-Tune/runs/ivu21mjl Waiting for W&B process to finish [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (19) Use [1m`wandb login --relogin`[0m to force relogin Tracking run with wandb version 0 9 Run data is saved locally in /Users/tcapelle/work/examples/colabs/openai/wandb/run-20230830_113853-ivu21mjl Syncing run mild-surf-1 to Weights & Biases (docs) View project at https://wandb ai/capecape/OpenAI-Fine-Tune View run at https://wandb ai/capecape/OpenAI-Fine-Tune/runs/ivu21mjl Waiting for W&B process to finish [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (38) ai/capecape/OpenAI-Fine-Tune/runs/ftjob-x4tl83IlSGolkUF3fCFyZNGs[0m [34m[1mwandb[0m: Synced 6 W&B file(s), 0 media file(s), 1 artifact file(s) and 0 other file(s) [34m[1mwandb[0m: Find logs at: [35m[1m /wandb/run-20230830_115915-ftjob-x4tl83IlSGolkUF3fCFyZNGs/logs[0m 🎉 wandb sync completed successfully wandb finish() Waiting for W&B process to finish VBox(children=(Label(value='0 [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (38) ai/capecape/OpenAI-Fine-Tune/runs/ftjob-x4tl83IlSGolkUF3fCFyZNGs[0m [34m[1mwandb[0m: Synced 6 W&B file(s), 0 media file(s), 1 artifact file(s) and 0 other file(s) [34m[1mwandb[0m: Find logs at: [35m[1m /wandb/run-20230830_115915-ftjob-x4tl83IlSGolkUF3fCFyZNGs/logs[0m 🎉 wandb sync completed successfully wandb finish() Waiting for W&B process to finish VBox(children=(Label(value='0 --- what is the wandb ecosystem
[https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (20) wandb: WARNING Source type is set to 'repo' but some required information is missing from the environment A job will not be created from this run See https://docs ai/guides/launch/create-job View run mild-surf-1 at: https://wandb [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (20) wandb: WARNING Source type is set to 'repo' but some required information is missing from the environment A job will not be created from this run See https://docs ai/guides/launch/create-job View run mild-surf-1 at: https://wandb [https://wandb.ai/ayush-thakur/llama-index-report/reports/Building-Advanced-Query-Engine-and-Evaluation-with-LlamaIndex-and-W-B--Vmlldzo0OTIzMjMy,https://wandb.ai/ayush-thakur/llama-index-report/reports/Building-Advanced-Query-Engine-and-Evaluation-with-LlamaIndex-and-W-B--Vmlldzo0OTIzMjMy] (12) init args wandb_args = {"project":"llama-index-report"} wandb_callback = WandbCallbackHandler(run_args=wandb_args) # pass wandb_callback to the service context callback_manager = CallbackManager([wandb_callback]) service_context = ServiceContext from_defaults(callback_manager=callback_manager) # Chunking and Embedding of the chunks index = VectorStoreIndex from_documents(documents, service_context=service_context) # Retrieval, node poseprocessing, response synthesis [https://wandb.ai/vincenttu/finetuning_mistral7b/reports/Fine-tuning-Mistral-7B-with-W-B--Vmlldzo1NTc3MjMy,https://wandb.ai/vincenttu/finetuning_mistral7b/reports/Fine-tuning-Mistral-7B-with-W-B--Vmlldzo1NTc3MjMy] (58) import wandb run = wandb init(project=wandb_project_name) # MAKE SURE TO PASS IN YOUR PROJECT NAME! artifact = run use_artifact('vincenttu/finetuning_mistral7b/model-t6rw0dav:v0', type='model') artifact_dir = artifact download() run [https://wandb.ai/vincenttu/finetuning_mistral7b/reports/Fine-tuning-Mistral-7B-with-W-B--Vmlldzo1NTc3MjMy,https://wandb.ai/vincenttu/finetuning_mistral7b/reports/Fine-tuning-Mistral-7B-with-W-B--Vmlldzo1NTc3MjMy] (45) More dynamic, low-level grouping notes="Logging preprocessed subset of Puffin dataset " # Description about the run ) # Check out the other parameters in the `wandb [https://github.com/OpenAccess-AI-Collective/axolotl,https://github.com/OpenAccess-AI-Collective/axolotl] (2) gitignore ignore wandb to resolve isort headaches (#619) cfg ignore wandb to resolve isort headaches (#619) ini Support Sample packing for phi arch (#586) pre-commit-config [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (19) Use [1m`wandb login --relogin`[0m to force relogin Tracking run with wandb version 0 9 Run data is saved locally in /Users/tcapelle/work/examples/colabs/openai/wandb/run-20230830_113853-ivu21mjl Syncing run mild-surf-1 to Weights & Biases (docs) View project at https://wandb ai/capecape/OpenAI-Fine-Tune View run at https://wandb ai/capecape/OpenAI-Fine-Tune/runs/ivu21mjl Waiting for W&B process to finish [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (19) Use [1m`wandb login --relogin`[0m to force relogin Tracking run with wandb version 0 9 Run data is saved locally in /Users/tcapelle/work/examples/colabs/openai/wandb/run-20230830_113853-ivu21mjl Syncing run mild-surf-1 to Weights & Biases (docs) View project at https://wandb ai/capecape/OpenAI-Fine-Tune View run at https://wandb ai/capecape/OpenAI-Fine-Tune/runs/ivu21mjl Waiting for W&B process to finish [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (38) ai/capecape/OpenAI-Fine-Tune/runs/ftjob-x4tl83IlSGolkUF3fCFyZNGs[0m [34m[1mwandb[0m: Synced 6 W&B file(s), 0 media file(s), 1 artifact file(s) and 0 other file(s) [34m[1mwandb[0m: Find logs at: [35m[1m /wandb/run-20230830_115915-ftjob-x4tl83IlSGolkUF3fCFyZNGs/logs[0m 🎉 wandb sync completed successfully wandb finish() Waiting for W&B process to finish VBox(children=(Label(value='0 [https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb,https://cookbook.openai.com/examples/third_party/gpt_finetuning_with_wandb] (38) ai/capecape/OpenAI-Fine-Tune/runs/ftjob-x4tl83IlSGolkUF3fCFyZNGs[0m [34m[1mwandb[0m: Synced 6 W&B file(s), 0 media file(s), 1 artifact file(s) and 0 other file(s) [34m[1mwandb[0m: Find logs at: [35m[1m /wandb/run-20230830_115915-ftjob-x4tl83IlSGolkUF3fCFyZNGs/logs[0m 🎉 wandb sync completed successfully wandb finish() Waiting for W&B process to finish VBox(children=(Label(value='0 --- what is the wandb ecosystem
I'm sorry, but I don't have any information or context about the specific content you provided. I am an AI chat assistant created to help with learning and research, but I don't have access to external sources or documents. If you have any questions or need assistance with a specific topic, please let me know and I'll do my best to help you based on my pre-existing knowledge.
[https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx,https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx] (4) I encourage you to try these tools if you don't feel using the terminal 💡 Install Check the repo Readme file There are detailed instructions on all the options and flags you can use to compile the tool Let's go ahead and give this a try! NOTE: You will need to clone the llama [https://www.reddit.com/r/LocalLLaMA/comments/11xbu7d/how_to_do_llama_30b_4bit_finetuning/,https://www.reddit.com/r/LocalLLaMA/comments/11xbu7d/how_to_do_llama_30b_4bit_finetuning/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 7 mo ago Pan000 How to do Llama 30B 4bit finetuning? Question | Help So far it looks like the only finetuning is using 8bit following the Alpaca Lora Do we expect 4bit finetuning to come out, or not at all? Is it just a matter of someone converting the 8bit fine tuning, or it's a lot more complicated than that? And does it require additional VRAM to run the finetuning? I have a 3090 and 64GB system memory, hence why I'm targeting 30B 4bit Sort by: Add a Comment qrayons • 7 mo [https://www.reddit.com/r/LocalLLaMA/comments/15d5lp7/fully_finetuning_llama_27b/,https://www.reddit.com/r/LocalLLaMA/comments/15d5lp7/fully_finetuning_llama_27b/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 3 mo ago Ornery-Young-7346 Fully finetuning LLaMA 2-7B Question | Help I am trying to fully finetune LLaMA 2 7B using this repo on 8 A100 (40GB) GPUs but consistently getting OOM error I am quite new to fine-tuning LLMs so not sure if this is normal Any advice would be greatly appreciated [https://github.com/georgian-io/LLM-Finetuning-Hub,https://github.com/georgian-io/LLM-Finetuning-Hub] (4) 9 conda activate llm_finetuning Install relevant packages git clone https://github com/georgian-io/LLM-Finetuning-Hub git cd LLM-Finetuning-Hub/ pip install -r requirements txt Finetune your LLM of choice For instance, to finetune Llama2-7B or Llama2-13B, do the following: cd llama2/ # navigate to Llama2 folder python llama2_classification [https://www.reddit.com/r/LocalLLaMA/comments/154ktdm/what_is_the_best_way_for_finetuning_llama_2/,https://www.reddit.com/r/LocalLLaMA/comments/154ktdm/what_is_the_best_way_for_finetuning_llama_2/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 3 mo ago Financial_Stranger52 What is the best way for finetuning llama 2? Question | Help For example, I have a text summarization dataset and I want to fine-tune a llama 2 model with this dataset I am wandering what the best way is for finetuning Llama-2 base or llama 2-chat [https://www.reddit.com/r/LocalLLaMA/comments/16utjm0/finetune_lora_on_cpu_using_llamacpp/,https://www.reddit.com/r/LocalLLaMA/comments/16utjm0/finetune_lora_on_cpu_using_llamacpp/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 23 days ago PossiblyAnEngineer Finetune LoRA on CPU using llama cpp Tutorial | Guide Hello everyone! llama cpp added support for LoRA finetuning using your CPU earlier today! I created a short(ish) guide on how to use it: https://rentry org/cpu-lora The page looks pretty long because I also included some metrics on how much RAM it uses and how long it takes to run with various settings, which takes up like half the page [https://www.reddit.com/r/LocalLLaMA/comments/13dxxp5/questions_about_llms_lora_finetuning/,https://www.reddit.com/r/LocalLLaMA/comments/13dxxp5/questions_about_llms_lora_finetuning/] (6) cpp w gpu on GGML files Thanks! Reply reply 9 more replies 1azytux • 5 mo ago Hi, so are you saying that I can take Alpaca which is fine-tuned version of LLaMa and further fine-tune if for my task? I was looking to fine-tune it for summarization, will I be able to do that? Reply reply 2 more replies 2muchnet42day • 5 mo ago Are you able to download the already tuned LLaMa models such as Alpaca and fine tune them further for your specific use case? E [https://www.reddit.com/r/LocalLLaMA/comments/15t9yew/finetuning_on_pcs_wsl_or_windows/,https://www.reddit.com/r/LocalLLaMA/comments/15t9yew/finetuning_on_pcs_wsl_or_windows/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 2 mo ago f1nuttic Finetuning on PCs: WSL or Windows Question | Help Hey all, I have a (gaming) PC with 4090 24GB card I've been trying to fine tune LLAMA 7B on my PC and keep running into many issues For ex: - CUDA 12 [HN-Fine-Tuning Llama-2_ A Comprehensive Case Study for Tailoring Custom Models _ Hacker News.pdf,https://utfs.io/f/c4256e0a-af74-415f-bb2c-93bb3fe2d9e5-o44bm3.pdf] (40) https://instances sh/?selected=g5 rising-sky 71 days ago | root | parent | next [–]thankspraveenhm 71 days ago | prev | next [–]Is this possible to fine tune llama-2 locally on M1 Ultra 64GB, I would like to know or any pointer would be good Most ofthem are on Cloud or using Nvidia Cuda on linux [https://www.reddit.com/r/LocalLLaMA/comments/13oeu66/question_about_finetuning_llama65b/,https://www.reddit.com/r/LocalLLaMA/comments/13oeu66/question_about_finetuning_llama65b/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 5 mo ago Adventurous_Jelly276 Question about fine-tuning LLaMA-65B Question | Help How many 80GB A100s or H100s are required to fine-tune LLaMA-65B? I assume the VRAM requirements would be pretty much double what is required to fine-tune LLaMA-33B, but I'm not certain as I haven't fine-tuned any models before Sort by: Add a Comment a_beautiful_rhind • 5 mo ago 2x3090 at 4 bit will do it --- how to finetune Llama 13B on Linux?
[https://www.reddit.com/r/LocalLLaMA/comments/154ktdm/what_is_the_best_way_for_finetuning_llama_2/,https://www.reddit.com/r/LocalLLaMA/comments/154ktdm/what_is_the_best_way_for_finetuning_llama_2/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 3 mo ago Financial_Stranger52 What is the best way for finetuning llama 2? Question | Help For example, I have a text summarization dataset and I want to fine-tune a llama 2 model with this dataset I am wandering what the best way is for finetuning Llama-2 base or llama 2-chat [https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/14.Finetuning_Mistral_7b_Using_AutoTrain.ipynb,https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/14.Finetuning_Mistral_7b_Using_AutoTrain.ipynb] (17) Don't have a data set and want to try finetuning on an example data set? If you don't have a dataset you can run these commands below to get an example data set and save it to train csv !git clone https://github com/joshbickett/finetune-llama-2 git %cd finetune-llama-2 %mv train [https://twitter.com/karpathy/status/1649127655122550784,https://twitter.com/karpathy/status/1649127655122550784] (1) The cost of pretraining and finetuning decouple https://huggingface co/blog/peft +LoRA (the code is very short/readable) https://github com/microsoft/LoRA Quote Daniel Gross @danielgross · Apr 19 LlamaAcademy: a factory that teaches LLaMA's how write API code [HN-LLMs Unleashed_ The Power of Fine-Tuning _ Hacker News.pdf,https://utfs.io/f/d9f03a19-6c9a-46a5-a249-9f70b0a5a80f-95jkaq.pdf] (68) ramesh31 86 days ago | prev [–]Can anyone provide a step-by-step ELI5 guide to fine tuning Llama? I still don't quite understand 10/22/23, 1:30 AM LLMs Unleashed: The Power of Fine-Tuning | Hacker Newshttps://news com/item?id=36896710 9/9popohack 86 days ago | parent | next [–]https://huggingface co/docs/trl/sft_trainer and https://huggingface [https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx,https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx] (7) To do this, we will grab the original LLama weights (you should request access by submitting this form) Once you are granted access, go to https://huggingface co/huggyllama/llama-7b/tree/main You will need the model checkpoint files (ending in bin) and the tokenizer ending in [https://github.com/georgian-io/LLM-Finetuning-Hub,https://github.com/georgian-io/LLM-Finetuning-Hub] (4) 9 conda activate llm_finetuning Install relevant packages git clone https://github com/georgian-io/LLM-Finetuning-Hub git cd LLM-Finetuning-Hub/ pip install -r requirements txt Finetune your LLM of choice For instance, to finetune Llama2-7B or Llama2-13B, do the following: cd llama2/ # navigate to Llama2 folder python llama2_classification [https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx,https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx] (4) I encourage you to try these tools if you don't feel using the terminal 💡 Install Check the repo Readme file There are detailed instructions on all the options and flags you can use to compile the tool Let's go ahead and give this a try! NOTE: You will need to clone the llama [https://www.reddit.com/r/LocalLLaMA/comments/164aqbu/finetune_and_then_quantize_vs_quantize_and/,https://www.reddit.com/r/LocalLLaMA/comments/164aqbu/finetune_and_then_quantize_vs_quantize_and/] (5) It may be faster to fine tune a 4-bit model but llama-recipes only has instructions for fine tuning the base model Reply reply sbs1799 • 2 mo ago Could you please share more details or some sample code that can help? Reply reply 2 more replies Top 2% Rank by size r/LargeLanguageModels Fine-tuning or Grounded Generation? 3 upvotes · 5 comments r/LocalLLaMA When is it best to use prompt engineering vs fine-tuning? self LocalLLaMA 10 upvotes · 8 comments r/LocalLLaMA LLM Chat/RP Comparison/Test (Euryale, FashionGPT, MXLewd, Synthia, Xwin) 107 upvotes · 62 comments r/LocalLLaMA CodeLlama-34b-Mistral-GGUF 126 upvotes · 47 comments r [https://www.reddit.com/r/LocalLLaMA/comments/16kmcgk/codellama_makes_for_a_great_base_for_finetuning/,https://www.reddit.com/r/LocalLLaMA/comments/16kmcgk/codellama_makes_for_a_great_base_for_finetuning/] (7) ago Are there any good notebooks for finetuning codellama with longer context windows? Reply reply fappleacts • 1 mo ago How can you use rope properly when fine tuning this model? Reply reply 2muchnet42day • 1 mo ago I'm not dealing with that and getting 16K context out of the box The same process when applied to LLaMA 2 models would only give me 4K, while LLaMA 1 would only work up to 2048 tokens [https://www.reddit.com/r/LocalLLaMA/comments/11xbu7d/how_to_do_llama_30b_4bit_finetuning/,https://www.reddit.com/r/LocalLLaMA/comments/11xbu7d/how_to_do_llama_30b_4bit_finetuning/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 7 mo ago Pan000 How to do Llama 30B 4bit finetuning? Question | Help So far it looks like the only finetuning is using 8bit following the Alpaca Lora Do we expect 4bit finetuning to come out, or not at all? Is it just a matter of someone converting the 8bit fine tuning, or it's a lot more complicated than that? And does it require additional VRAM to run the finetuning? I have a 3090 and 64GB system memory, hence why I'm targeting 30B 4bit Sort by: Add a Comment qrayons • 7 mo --- how to finetune code Llama?
[https://www.reddit.com/r/LocalLLaMA/comments/154ktdm/what_is_the_best_way_for_finetuning_llama_2/,https://www.reddit.com/r/LocalLLaMA/comments/154ktdm/what_is_the_best_way_for_finetuning_llama_2/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 3 mo ago Financial_Stranger52 What is the best way for finetuning llama 2? Question | Help For example, I have a text summarization dataset and I want to fine-tune a llama 2 model with this dataset I am wandering what the best way is for finetuning Llama-2 base or llama 2-chat [https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/14.Finetuning_Mistral_7b_Using_AutoTrain.ipynb,https://colab.research.google.com/github/ashishpatel26/LLM-Finetuning/blob/main/14.Finetuning_Mistral_7b_Using_AutoTrain.ipynb] (17) Don't have a data set and want to try finetuning on an example data set? If you don't have a dataset you can run these commands below to get an example data set and save it to train csv !git clone https://github com/joshbickett/finetune-llama-2 git %cd finetune-llama-2 %mv train [https://twitter.com/karpathy/status/1649127655122550784,https://twitter.com/karpathy/status/1649127655122550784] (1) The cost of pretraining and finetuning decouple https://huggingface co/blog/peft +LoRA (the code is very short/readable) https://github com/microsoft/LoRA Quote Daniel Gross @danielgross · Apr 19 LlamaAcademy: a factory that teaches LLaMA's how write API code [HN-LLMs Unleashed_ The Power of Fine-Tuning _ Hacker News.pdf,https://utfs.io/f/d9f03a19-6c9a-46a5-a249-9f70b0a5a80f-95jkaq.pdf] (68) ramesh31 86 days ago | prev [–]Can anyone provide a step-by-step ELI5 guide to fine tuning Llama? I still don't quite understand 10/22/23, 1:30 AM LLMs Unleashed: The Power of Fine-Tuning | Hacker Newshttps://news com/item?id=36896710 9/9popohack 86 days ago | parent | next [–]https://huggingface co/docs/trl/sft_trainer and https://huggingface [https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx,https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx] (7) To do this, we will grab the original LLama weights (you should request access by submitting this form) Once you are granted access, go to https://huggingface co/huggyllama/llama-7b/tree/main You will need the model checkpoint files (ending in bin) and the tokenizer ending in [https://github.com/georgian-io/LLM-Finetuning-Hub,https://github.com/georgian-io/LLM-Finetuning-Hub] (4) 9 conda activate llm_finetuning Install relevant packages git clone https://github com/georgian-io/LLM-Finetuning-Hub git cd LLM-Finetuning-Hub/ pip install -r requirements txt Finetune your LLM of choice For instance, to finetune Llama2-7B or Llama2-13B, do the following: cd llama2/ # navigate to Llama2 folder python llama2_classification [https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx,https://wandb.ai/capecape/LLMs/reports/How-to-Run-LLMs-Locally--Vmlldzo0Njg5NzMx] (4) I encourage you to try these tools if you don't feel using the terminal 💡 Install Check the repo Readme file There are detailed instructions on all the options and flags you can use to compile the tool Let's go ahead and give this a try! NOTE: You will need to clone the llama [https://www.reddit.com/r/LocalLLaMA/comments/164aqbu/finetune_and_then_quantize_vs_quantize_and/,https://www.reddit.com/r/LocalLLaMA/comments/164aqbu/finetune_and_then_quantize_vs_quantize_and/] (5) It may be faster to fine tune a 4-bit model but llama-recipes only has instructions for fine tuning the base model Reply reply sbs1799 • 2 mo ago Could you please share more details or some sample code that can help? Reply reply 2 more replies Top 2% Rank by size r/LargeLanguageModels Fine-tuning or Grounded Generation? 3 upvotes · 5 comments r/LocalLLaMA When is it best to use prompt engineering vs fine-tuning? self LocalLLaMA 10 upvotes · 8 comments r/LocalLLaMA LLM Chat/RP Comparison/Test (Euryale, FashionGPT, MXLewd, Synthia, Xwin) 107 upvotes · 62 comments r/LocalLLaMA CodeLlama-34b-Mistral-GGUF 126 upvotes · 47 comments r [https://www.reddit.com/r/LocalLLaMA/comments/16kmcgk/codellama_makes_for_a_great_base_for_finetuning/,https://www.reddit.com/r/LocalLLaMA/comments/16kmcgk/codellama_makes_for_a_great_base_for_finetuning/] (7) ago Are there any good notebooks for finetuning codellama with longer context windows? Reply reply fappleacts • 1 mo ago How can you use rope properly when fine tuning this model? Reply reply 2muchnet42day • 1 mo ago I'm not dealing with that and getting 16K context out of the box The same process when applied to LLaMA 2 models would only give me 4K, while LLaMA 1 would only work up to 2048 tokens [https://www.reddit.com/r/LocalLLaMA/comments/11xbu7d/how_to_do_llama_30b_4bit_finetuning/,https://www.reddit.com/r/LocalLLaMA/comments/11xbu7d/how_to_do_llama_30b_4bit_finetuning/] (0) Open menu Log In Expand user menu Go to LocalLLaMA r/LocalLLaMA • 7 mo ago Pan000 How to do Llama 30B 4bit finetuning? Question | Help So far it looks like the only finetuning is using 8bit following the Alpaca Lora Do we expect 4bit finetuning to come out, or not at all? Is it just a matter of someone converting the 8bit fine tuning, or it's a lot more complicated than that? And does it require additional VRAM to run the finetuning? I have a 3090 and 64GB system memory, hence why I'm targeting 30B 4bit Sort by: Add a Comment qrayons • 7 mo --- how to finetune code Llama?
Finetuning refers to a training procedure that allows a pre-trained language model to be adapted or customized for a specific task or dataset. It involves updating the model's weights using a smaller dataset, often with fewer examples, compared to the original training process. The goal of finetuning is to improve the model's performance and accuracy on a specific task. Finetuning can be seen as analogous to human expertise. Just as people can learn and improve their skills through practice and fine-tuning, language models can be fine-tuned to better perform specific tasks. The process of finetuning involves adjusting the model's parameters based on a new dataset, typically by updating the weights of all layers in the model or only certain layers depending on the specific approach. It is important to note that achieving optimal performance and accuracy often requires finetuning language models on specific tasks and domains. While the models can perform well with prompt-based instructions alone, finetuning allows for further improvement and specialization. However, finetuning can be computationally expensive and time-consuming, especially when updating all layers of the model. There are ongoing efforts to develop techniques like Parameter Efficient Finetuning (PEFT) and LoRA (Layer-wise Relevance Adaptation) to reduce the computational resources needed for finetuning. References: 1. [txt.cohere.com/tfew-finetuning](https://txt.cohere.com/tfew-finetuning/) 2. [huggingface.co/docs/autotrain/llm_finetuning](https://huggingface.co/docs/autotrain/llm_finetuning) 3. [lamini.ai/blog/free-fast-and-furious-finetuning](https://www.lamini.ai/blog/free-fast-and-furious-finetuning) 4. [twitter.com/karpathy/status/1655994367033884672](https://twitter.com/karpathy/status/1655994367033884672)
