GPTQ-for-LLaMa-API
text-generation-inference
GPTQ-for-LLaMa-API | text-generation-inference | |
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5 | 29 | |
40 | 7,995 | |
- | 7.5% | |
4.7 | 9.6 | |
12 months ago | 7 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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GPTQ-for-LLaMa-API
- Alternative ways for running models locally and hosting APIs
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Can someone explain why there isn't a good interface for the oobabooga api in langchain?
oobabooga has to support way too many models, so making the whole thing unnecessarily complicated. If you have some development experience, maybe you would build your own API in a few lines of Python code. It's not hard if you build from scratch and learn along the way. I have built some example repositories for hosting GPTQ-related models. You can have a look at them. https://github.com/mzbac/GPTQ-for-LLaMa-API https://github.com/mzbac/gptq-cuda-api
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Looking to selfhost Llama on remote server, could use some help
I ran this https://github.com/mzbac/GPTQ-for-LLaMa-API for my home server. It should be easy enough to create a Dockerfile and make it hostable via Docker.
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How do I load a gptq LLaMA model (Vicuna) in .safetensors format?
If you have some experience with Python, you can take a look at my repo. It only has the minimal logic of how to load a GPTQ model and serve it as an API. https://github.com/mzbac/GPTQ-for-LLaMa-API
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Just create a repository to show how to serve GPTQ model via an API
Hopefully, it will make it easier for any developer who wants to build some integration with their app. https://github.com/mzbac/GPTQ-for-LLaMa-API
text-generation-inference
- FLaNK AI-April 22, 2024
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Zephyr 141B, a Mixtral 8x22B fine-tune, is now available in Hugging Chat
I wanted to write that TGI inference engine is not Open Source anymore, but they have reverted the license back to Apache 2.0 for the new version TGI v2.0: https://github.com/huggingface/text-generation-inference/rel...
Good news!
- Hugging Face reverts the license back to Apache 2.0
- HuggingFace text-generation-inference is reverting to Apache 2.0 License
- FLaNK Stack 05 Feb 2024
- Is there any open source app to load a model and expose API like OpenAI?
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AI Code assistant for about 50-70 users
Setting up a server for multiple users is very different from setting up LLM for yourself. A safe bet would be to just use TGI, which supports continuous batching and is very easy to run via Docker on your server. https://github.com/huggingface/text-generation-inference
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LocalPilot: Open-source GitHub Copilot on your MacBook
Okay, I actually got local co-pilot set up. You will need these 4 things.
1) CodeLlama 13B or another FIM model https://huggingface.co/codellama/CodeLlama-13b-hf. You want "Fill in Middle" models because you're looking at context on both sides of your cursor.
2) HuggingFace llm-ls https://github.com/huggingface/llm-ls A large language mode Language Server (is this making sense yet)
3) HuggingFace inference framework. https://github.com/huggingface/text-generation-inference At least when I tested you couldn't use something like llama.cpp or exllama with the llm-ls, so you need to break out the heavy duty badboy HuggingFace inference server. Just config and run. Now config and run llm-ls.
4) Okay, I mean you need an editor. I just tried nvim, and this was a few weeks ago, so there may be better support. My expereicen was that is was full honest to god copilot. The CodeLlama models are known to be quite good for its size. The FIM part is great. Boilerplace works so much easier with the surrounding context. I'd like to see more models released that can work this way.
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Mistral 7B Paper on ArXiv
A simple microservice would be https://github.com/huggingface/text-generation-inference .
Works flawlessly in Docker on my Windows machine, which is extremely shocking.
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best way to serve llama V2 (llama.cpp VS triton VS HF text generation inference)
I am wondering what is the best / most cost-efficient way to serve llama V2. - llama.cpp (is it production ready or just for playing around?) ? - Triton inference server ? - HF text generation inference ?
What are some alternatives?
gptq-cuda-api
llama-cpp-python - Python bindings for llama.cpp
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
learn-langchain
exllama - A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
basaran - Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
AgentOoba - An autonomous AI agent extension for Oobabooga's web ui
FlexGen - Running large language models on a single GPU for throughput-oriented scenarios.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
vllm - A high-throughput and memory-efficient inference and serving engine for LLMs