gpt-llama.cpp
basaran
gpt-llama.cpp | basaran | |
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12 | 22 | |
587 | 1,281 | |
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8.2 | 10.0 | |
11 months ago | 4 months ago | |
JavaScript | Python | |
MIT License | MIT License |
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gpt-llama.cpp
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Attempt to run Llama on a remote server with chatbot-ui
hi! I really like the solution https://github.com/keldenl/gpt-llama.cpp which helps to deploy https://github.com/mckaywrigley/chatbot-ui on the local model. I am running this together with Wizard7b or 13b locally and it works fine, but when I tried to upload to a remote server I met an error.
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Introducing Basaran: self-hosted open-source alternative to the OpenAI text completion API
sounds like you’re asking for exactly this? https://github.com/keldenl/gpt-llama.cpp
- LLaMA and AutoAPI?
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New big update to GPTNicheFinder: better trends analysis and scoring system, cleaned up UI and verbose in the terminal for people who want to see what is going on and to verify the results
I salut you good sir. This is an amazing idea. I don't have time but it will be interesting idea to use this wrapper https://github.com/keldenl/gpt-llama.cpp which simulates GPT endpoint for local lama, so basically we can have amazing tool for completely free use. If somebody test it please let me know underneath my comment!
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I build an AI powered writing tools, an AI co-author
I would gladly buy your product to run with a local model, like Vicuna ggml , also see https://github.com/keldenl/gpt-llama.cpp/
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Serge... Just works
possible through fastllama in python or gpt-llama.cpp an API wrapper around llama.cpp
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Embeddings?
https://github.com/keldenl/gpt-llama.cpp supports embeddings, and it even takes in openai type requests and returns openai compatible responses!
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I built a completely Local AutoGPT with the help of GPT-llama running Vicuna-13B
https://github.com/keldenl/gpt-llama.cpp
- I build a completely Local and portable AutoGPT with the help of gpt-llama, running on Vicuna-13b
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Adding Long-Term Memory to Custom LLMs: Let's Tame Vicuna Together!
There's a (kind of) working Auto-GPT solution that uses Vicuna https://github.com/keldenl/gpt-llama.cpp/blob/master/docs/Auto-GPT-setup-guide.md
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?
llama_index - LlamaIndex is a data framework for your LLM applications
text-generation-inference - Large Language Model Text Generation Inference
Auto-LLM-Local - Created my own python script similar to AutoGPT where you supply a local llm model like alpaca13b (The main one I use), and the script can access the supplied tools to achieve your objective. Code fully works as far as I can tell. Takes me 5 minutes per chain on my slow laptop.
openai-chatgpt-opentranslator - Python command that uses openai to perform text translations
long_term_memory - A gradio web UI for running Large Language Models like GPT-J 6B, OPT, GALACTICA, LLaMA, and Pygmalion.
AutoGPTQ - An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
llm-foundry - LLM training code for Databricks foundation models
langchain - 🦜🔗 Build context-aware reasoning applications
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM