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hfl/chinese-alpaca-2-1.3b-rlhf-gguf
chinese-alpaca-2-1.3b-rlhf-gguf is a machine learning model from hfl. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This repository contains GGUF-v3 version (llama.cpp compatible) of Chinese-Alpaca-2-1.3B-RLHF, which is tuned on Chinese-Alpaca-2-1.3B with RLHF using DeepSpeed-Chat.
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From the Hugging Face model README
This repository contains GGUF-v3 version (llama.cpp compatible) of Chinese-Alpaca-2-1.3B-RLHF, which is tuned on Chinese-Alpaca-2-1.3B with RLHF using DeepSpeed-Chat.
The optimal context length is 1K for this model. Specify -c 1024 when using with llama.cpp
Metric: PPL, lower is better
| Quant | original | imatrix (-im) |
|---|---|---|
| Q2_K | 20.1066 +/- 0.29236 | 18.8209 +/- 0.27561 |
| Q3_K | 16.9214 +/- 0.26133 | 16.5729 +/- 0.25706 |
| Q4_0 | 15.8056 +/- 0.23749 | - |
| Q4_K | 16.1579 +/- 0.25064 | 15.7746 +/- 0.24476 |
| Q5_0 | 15.4528 +/- 0.23911 | - |
| Q5_K | 15.3198 +/- 0.23627 | 15.4791 +/- 0.23959 |
| Q6_K | 15.3718 +/- 0.23764 | 15.2572 +/- 0.23549 |
| Q8_0 | 15.3302 +/- 0.23727 | - |
| F16 | 15.3291 +/- 0.23728 | - |
The model with -im suffix is generated with important matrix, which has generally better performance (not always though).
For full model in HuggingFace format, please see: https://huggingface.co/hfl/chinese-alpaca-2-1.3b-rlhf
Please refer to https://github.com/ymcui/Chinese-LLaMA-Alpaca-2/ for more details.