basaran
alpaca_lora_4bit
basaran | alpaca_lora_4bit | |
---|---|---|
22 | 41 | |
1,281 | 529 | |
- | - | |
10.0 | 8.6 | |
4 months ago | 6 months ago | |
Python | Python | |
MIT License | MIT License |
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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.
alpaca_lora_4bit
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Open Inference Engine Comparison | Features and Functionality of TGI, vLLM, llama.cpp, and TensorRT-LLM
For training there is also https://github.com/johnsmith0031/alpaca_lora_4bit
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Quantized 8k Context Base Models for 4-bit Fine Tuning
I've been trying to fine tune an erotica model on some large context chat history (reverse proxy logs) and a literotica-instruct dataset I made, with a max context of 8k. The large context size eats a lot of VRAM so I've been trying to find the most efficient way to experiment considering I'd like to do multiple runs to test some ideas. So I'm going to try and use https://github.com/johnsmith0031/alpaca_lora_4bit, which is supposed to train faster and use less memory than qlora.
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A simple repo for fine-tuning LLMs with both GPTQ and bitsandbytes quantization. Also supports ExLlama for inference for the best speed.
Follow up the popular work of u/tloen alpaca-lora, I wrapped the setup of alpaca_lora_4bit to add support for GPTQ training in form of installable pip packages. You can perform training and inference with multiple quantizations method to compare the results.
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Does we still need monkey patch with exllama loader for lora?
" Using LoRAs with GPTQ-for-LLaMa This requires using a monkey patch that is supported by this web UI: https://github.com/johnsmith0031/alpaca_lora_4bit"
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Why isn’t QLoRA being used more widely for fine tuning models?
4-bit GPTQ LoRA training was available since early April. I did not see any comparison to it in the QLoRA paper or even a mention, so it makes me think they were not aware it already existed.
- Fine-tuning with alpaca_lora_4bit on 8k context SuperHOT models
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Any guide/intro to fine-tuning anywhere?
https://github.com/johnsmith0031/alpaca_lora_4bit is still the SOTA - Faster than qlora, trains on a GPTQ base.
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"Samantha-33B-SuperHOT-8K-GPTQ" now that's a great name for a true model.
I would also like to know how one would finetune this in 4 bit? I think one could take the merged 8K PEFT with the LLaMA weights, and then quantize it to 4 bit, and then train with https://github.com/johnsmith0031/alpaca_lora_4bit ?
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Help with QLoRA
I was under the impression that you just git clone this repo into text-generation-webui/repositories (so you would have GPTQ_for_Llama and alpaca_lora_4bit in the folder), and then just load with monkey patch. Is that not correct? I also tried just downloading alpaca_lora_4bit on its own, git cloning text-gen-webui within it, and installing requirements.txt for both and running with monkey patch. I was following the sections of alpaca_lora_4bit, "Text Generation Webui Monkey Patch" and "monkey patch inside webui"
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Best uncensored model for an a6000
I dont have any familiarity with esxi, but I can say that there are quite a few posts about people doing it on proxmox. I've currently got a machine with 2x3090 passing through to VM's. When I'm training, I pass them both through to the same VM and can do lora 4-bit training on llama33 using https://github.com/johnsmith0031/alpaca_lora_4bit. Then, at inference time, I run a single card into a different VM, and have an extra card available for experimentation.
What are some alternatives?
text-generation-inference - Large Language Model Text Generation Inference
flash-attention - Fast and memory-efficient exact attention
openai-chatgpt-opentranslator - Python command that uses openai to perform text translations
qlora - QLoRA: Efficient Finetuning of Quantized LLMs
AutoGPTQ - An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
StableLM - StableLM: Stability AI Language Models
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
safetensors - Simple, safe way to store and distribute tensors
llm-foundry - LLM training code for Databricks foundation models
alpaca-lora - Instruct-tune LLaMA on consumer hardware
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.