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mode 100644 index 0000000..24293a2 --- /dev/null +++ b/README.md @@ -0,0 +1,65 @@ +--- +base_model: modelscope/Llama3-Chinese-8B-Instruct-Agent-v1 +language: +- en +library_name: transformers +license: llama3 +quantized_by: mradermacher +--- +## About + + + + + + +static quants of https://huggingface.co/modelscope/Llama3-Chinese-8B-Instruct-Agent-v1 + + +weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. +## Usage + +If you are unsure how to use GGUF files, refer to one of [TheBloke's +READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for +more details, including on how to concatenate multi-part files. + +## Provided Quants + +(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) + +| Link | Type | Size/GB | Notes | +|:-----|:-----|--------:|:------| +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q2_K.gguf) | Q2_K | 3.3 | | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q3_K_S.gguf) | Q3_K_S | 3.8 | | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q3_K_L.gguf) | Q3_K_L | 4.4 | | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.IQ4_XS.gguf) | IQ4_XS | 4.6 | | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.8 | fast on arm, low quality | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q5_K_S.gguf) | Q5_K_S | 5.7 | | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q5_K_M.gguf) | Q5_K_M | 5.8 | | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q6_K.gguf) | Q6_K | 6.7 | very good quality | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality | +| [GGUF](https://huggingface.co/mradermacher/Llama3-Chinese-8B-Instruct-Agent-v1-GGUF/resolve/main/Llama3-Chinese-8B-Instruct-Agent-v1.f16.gguf) | f16 | 16.2 | 16 bpw, overkill | + +Here is a handy graph by ikawrakow comparing some lower-quality quant +types (lower is better): + +![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) + +And here are Artefact2's thoughts on the matter: +https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 + +## FAQ / Model Request + +See https://huggingface.co/mradermacher/model_requests for some answers to +questions you might have and/or if you want some other model quantized. + +## Thanks + +I thank my company, [nethype GmbH](https://www.nethype.de/), for letting +me use its servers and providing upgrades to my workstation to enable +this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to. + +