Instructions to use BoyangZ/llama3_chinese_basemode_ftv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BoyangZ/llama3_chinese_basemode_ftv1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="BoyangZ/llama3_chinese_basemode_ftv1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("BoyangZ/llama3_chinese_basemode_ftv1")
model = AutoModelForCausalLM.from_pretrained("BoyangZ/llama3_chinese_basemode_ftv1")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use BoyangZ/llama3_chinese_basemode_ftv1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "BoyangZ/llama3_chinese_basemode_ftv1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BoyangZ/llama3_chinese_basemode_ftv1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/BoyangZ/llama3_chinese_basemode_ftv1

SGLang

How to use BoyangZ/llama3_chinese_basemode_ftv1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "BoyangZ/llama3_chinese_basemode_ftv1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BoyangZ/llama3_chinese_basemode_ftv1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "BoyangZ/llama3_chinese_basemode_ftv1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BoyangZ/llama3_chinese_basemode_ftv1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use BoyangZ/llama3_chinese_basemode_ftv1 with Docker Model Runner:
```
docker model run hf.co/BoyangZ/llama3_chinese_basemode_ftv1
```

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Check out the documentation for more information.

language: - zh license: apache-2.0 metrics: - accuracy pipeline_tag: text-generation

It's not a chat model, just using Wizard-LM-Chinese-instruct-evol datesets training with several steps for test the model typical Chinese skill， this is version1, will release version2 for more long context windows and Chat model

Train scenario:

2k context

datasets:Wizard-LM-Chinese-instruct-evol

batchsize:8

steps:500

epchos:2

How to use?

Follow common huggingface-api is enough or using other framework like VLLM, support continue training.

import transformers import torch

model_id = "BoyangZ/llama3-chinese"

pipeline = transformers.pipeline( "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto" ) pipeline("川普和拜登谁能赢得大选??")

[{'generated_text': '川普和拜登谁能赢得大选?](https://www.voachinese.com'}]

import torch from transformers import AutoModelForCausalLM, AutoTokenizer torch.set_default_device("cuda") model = AutoModelForCausalLM.from_pretrained("BoyangZ/llama3-chinese", torch_dtype="auto", trust_remote_code=True) tokenizer = AutoTokenizer.from_pretrained("BoyangZ/llama3-chinese", trust_remote_code=True) inputs = tokenizer( "川普和拜登一起竞选，美国总统,谁获胜的几率大,分析一下?", return_tensors="pt", return_attention_mask=False ) outputs = model.generate(**inputs, max_length=200) text = tokenizer.batch_decode(outputs)[0] print(text)

Wechat:18618377979, Gmail:zhouboyang1983@gmail.com

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Safetensors

Model size

8B params

Tensor type

F32