Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


Llama3-Chinese-8B-Instruct - GGUF
- Model creator: https://huggingface.co/FlagAlpha/
- Original model: https://huggingface.co/FlagAlpha/Llama3-Chinese-8B-Instruct/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Llama3-Chinese-8B-Instruct.Q2_K.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q2_K.gguf) | Q2_K | 2.96GB |
| [Llama3-Chinese-8B-Instruct.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.IQ3_XS.gguf) | IQ3_XS | 3.28GB |
| [Llama3-Chinese-8B-Instruct.IQ3_S.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.IQ3_S.gguf) | IQ3_S | 1.58GB |
| [Llama3-Chinese-8B-Instruct.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q3_K_S.gguf) | Q3_K_S | 0.35GB |
| [Llama3-Chinese-8B-Instruct.IQ3_M.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.IQ3_M.gguf) | IQ3_M | 3.52GB |
| [Llama3-Chinese-8B-Instruct.Q3_K.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q3_K.gguf) | Q3_K | 3.74GB |
| [Llama3-Chinese-8B-Instruct.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q3_K_M.gguf) | Q3_K_M | 3.74GB |
| [Llama3-Chinese-8B-Instruct.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q3_K_L.gguf) | Q3_K_L | 4.03GB |
| [Llama3-Chinese-8B-Instruct.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.IQ4_XS.gguf) | IQ4_XS | 4.18GB |
| [Llama3-Chinese-8B-Instruct.Q4_0.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q4_0.gguf) | Q4_0 | 4.34GB |
| [Llama3-Chinese-8B-Instruct.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.IQ4_NL.gguf) | IQ4_NL | 4.38GB |
| [Llama3-Chinese-8B-Instruct.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q4_K_S.gguf) | Q4_K_S | 4.37GB |
| [Llama3-Chinese-8B-Instruct.Q4_K.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q4_K.gguf) | Q4_K | 4.58GB |
| [Llama3-Chinese-8B-Instruct.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q4_K_M.gguf) | Q4_K_M | 4.58GB |
| [Llama3-Chinese-8B-Instruct.Q4_1.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q4_1.gguf) | Q4_1 | 4.78GB |
| [Llama3-Chinese-8B-Instruct.Q5_0.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q5_0.gguf) | Q5_0 | 5.21GB |
| [Llama3-Chinese-8B-Instruct.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q5_K_S.gguf) | Q5_K_S | 5.21GB |
| [Llama3-Chinese-8B-Instruct.Q5_K.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q5_K.gguf) | Q5_K | 5.34GB |
| [Llama3-Chinese-8B-Instruct.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q5_K_M.gguf) | Q5_K_M | 5.34GB |
| [Llama3-Chinese-8B-Instruct.Q5_1.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q5_1.gguf) | Q5_1 | 5.65GB |
| [Llama3-Chinese-8B-Instruct.Q6_K.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q6_K.gguf) | Q6_K | 6.14GB |
| [Llama3-Chinese-8B-Instruct.Q8_0.gguf](https://huggingface.co/RichardErkhov/FlagAlpha_-_Llama3-Chinese-8B-Instruct-gguf/blob/main/Llama3-Chinese-8B-Instruct.Q8_0.gguf) | Q8_0 | 7.95GB |




Original model description:
---
license: apache-2.0
tags:
- llama3
- chinese
---

# Llama3-Chinese-8B-Instruct

Llama3-Chinese-8B-Instruct基于Llama3-8B中文微调对话模型，由Llama中文社区和AtomEcho（原子回声）联合研发，我们会持续提供更新的模型参数，模型训练过程见 [https://llama.family](https://llama.family)。

模型的部署、训练、微调等方法详见Llama中文社区GitHub仓库：[https://github.com/LlamaFamily/Llama-Chinese](https://github.com/LlamaFamily/Llama-Chinese)

## 如何使用

```
import transformers
import torch


model_id = "FlagAlpha/Llama3-Chinese-8B-Instruct"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.float16},
    device="cuda",
)


messages = [{"role": "system", "content": ""}]

messages.append(
                {"role": "user", "content": "介绍一下机器学习"}
            )

prompt = pipeline.tokenizer.apply_chat_template(
        messages, 
        tokenize=False, 
        add_generation_prompt=True
    )

terminators = [
        pipeline.tokenizer.eos_token_id,
        pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
    ]
outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.6,
    top_p=0.9
)

content = outputs[0]["generated_text"][len(prompt):]

print(content)
```