localmodels / Vicuna-7B-v1.3-GPTQ

huggingface.co
Total runs: 5
24-hour runs: 0
7-day runs: -1
30-day runs: 0
Model's Last Updated: July 13 2023
text-generation

Introduction of Vicuna-7B-v1.3-GPTQ

Model Details of Vicuna-7B-v1.3-GPTQ

Vicuna 7B v1.3 GPTQ

From LMSYS: https://huggingface.co/lmsys/vicuna-7b-v1.3


Branch Bits Group Size Act Order (desc_act) File Size ExLlama Compatible? Made With Description
vicuna-7b-v1.3-GPTQ-4bit-128g.no-act.order 4 128 False 4.00 GB True GPTQ-for-LLaMa Most compatible. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa.

Vicuna Model Card

Model Details

Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.

  • Developed by: LMSYS
  • Model type: An auto-regressive language model based on the transformer architecture.
  • License: Non-commercial license
  • Finetuned from model: LLaMA .
Model Sources
Uses

The primary use of Vicuna is research on large language models and chatbots. The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Command line interface: https://github.com/lm-sys/FastChat#vicuna-weights .
APIs (OpenAI API, Huggingface API): https://github.com/lm-sys/FastChat/tree/main#api .

Training Details

Vicuna v1.3 is fine-tuned from LLaMA with supervised instruction fine-tuning. The training data is around 140K conversations collected from ShareGPT.com. See more details in the "Training Details of Vicuna Models" section in the appendix of this paper .

Evaluation

Vicuna is evaluated with standard benchmarks, human preference, and LLM-as-a-judge. See more details in this paper and leaderboard .

Difference between different versions of Vicuna

See vicuna_weights_version.md

Runs of localmodels Vicuna-7B-v1.3-GPTQ on huggingface.co

5
Total runs
0
24-hour runs
0
3-day runs
-1
7-day runs
0
30-day runs

More Information About Vicuna-7B-v1.3-GPTQ huggingface.co Model

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Vicuna-7B-v1.3-GPTQ install

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