Instructions to use mingdali/ChatTruth-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mingdali/ChatTruth-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mingdali/ChatTruth-7B", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mingdali/ChatTruth-7B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mingdali/ChatTruth-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mingdali/ChatTruth-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mingdali/ChatTruth-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mingdali/ChatTruth-7B
- SGLang
How to use mingdali/ChatTruth-7B 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 "mingdali/ChatTruth-7B" \ --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": "mingdali/ChatTruth-7B", "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 "mingdali/ChatTruth-7B" \ --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": "mingdali/ChatTruth-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mingdali/ChatTruth-7B with Docker Model Runner:
docker model run hf.co/mingdali/ChatTruth-7B
示例代码报错
很抱歉打扰,不知道为什么,在下载好了模型之后,运行示例代码会有报错
runyu.cai@star-SYS-4029GP-TRT:~/ChatTruth-7B$ python3 demo.py
Traceback (most recent call last):
File "/home/runyu.cai/ChatTruth-7B/demo.py", line 7, in
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
File "/usr/local/lib/python3.10/dist-packages/transformers/models/auto/tokenization_auto.py", line 774, in from_pretrained
return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py", line 2028, in from_pretrained
return cls._from_pretrained(
File "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py", line 2260, in _from_pretrained
tokenizer = cls(*init_inputs, **init_kwargs)
File "/home/runyu.cai/.cache/huggingface/modules/transformers_modules/ChatTruth-7B/tokenization_qwen.py", line 121, in init
super().init(**kwargs)
File "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils.py", line 367, in init
self._add_tokens(
File "/home/runyu.cai/.cache/huggingface/modules/transformers_modules/ChatTruth-7B/tokenization_qwen.py", line 224, in _add_tokens
if surface_form not in SPECIAL_TOKENS + self.IMAGE_ST:
AttributeError: 'QWenTokenizer' object has no attribute 'IMAGE_ST'
这是为什么呢?
对齐版本或者 tokenization_qwen.py 121行放到138行