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basaran
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mutate
basaran
- OpenLLM
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Langchain and self hosted LLaMA hosted API
What are the current best "no reinventing the wheel" approaches to have Langchain use an LLM through a locally hosted REST API, the likes of Oobabooga or hyperonym/basaran with streaming support for 4-bit GPTQ?
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Run and create custom ChatGPT-like bots with OpenChat
Disclaimer: I am curating LLM-tools on github [1]
A few thoughts:
* allow for custom endpoint URLs, this way people can use open source LLMs with a fake openAI API backend like basaran[2] or llama-api-server[3]
* look into better embedding methods for info-retrieval like InstructorEmbeddings or Document Summary Index
* Don't use a single embedding per content item, use multiple to increase retrieval quality
1 https://github.com/underlines/awesome-marketing-datascience/...
2 https://github.com/hyperonym/basaran
3 https://github.com/iaalm/llama-api-server
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1-Jun-2023
open-source alternative to the OpenAI text completion API (https://github.com/hyperonym/basaran)
- Introducing Basaran: self-hosted open-source alternative to the OpenAI text completion API
- Basaran is an open-source alternative to the OpenAI text completion API
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Ask HN: What's the best self hosted/local alternative to GPT-4?
Guanaco-65B[0] using Basaran[1] for your OpenAI compatible API. You can use any ChatGPT front-end which lets you change the OpenAI endpoint URL.
[0] An fp4 finetune of LLaMA-30B by Tim Dettmers
[1] https://github.com/hyperonym/basaran
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Are all the finetunes stupid?
For lm-eval, I think you'd either need to take GPTQ's inference script and shim it into a model: https://github.com/EleutherAI/lm-evaluation-harness/tree/master/lm_eval/models or you might be able to use a project like https://github.com/hyperonym/basaran and then you could use the gpt3 model...
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Using the API in Node
There are also: - Basaran repo: "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". "...Compatibility with OpenAI API and client libraries..."; - llama-cpp-python repo: "Simple Python bindings for @ggerganov's llama.cpp library...". "...OpenAI-like API...".
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Researcher looking for help with how to prepare a finetuning dataset for models like Bloomz and Cerebras-GPT
I want to start with a totally freely available model, so again, that excludes things like LLaMA where the weights are only available through a wait list. The two models that most get my attention and (I think, and hope) fit my criteria of open availability are Cerebras-GPT (13b) and Bloomz (7b). The tools to process and fine-tune that seem most feasible to me, from my limit knowledge, are xturing and basaran.
What are some alternatives?
question_extractor - Generate question/answer training pairs out of raw text.
text-generation-inference - Large Language Model Text Generation Inference
refinery - The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.
openai-chatgpt-opentranslator - Python command that uses openai to perform text translations
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
AutoGPTQ - An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
GODEL - Large-scale pretrained models for goal-directed dialog
llm-foundry - LLM training code for Databricks foundation models
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
lmql - A language for constraint-guided and efficient LLM programming.