Instructions to use TsinghuaAI/CPM-Generate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TsinghuaAI/CPM-Generate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TsinghuaAI/CPM-Generate")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TsinghuaAI/CPM-Generate") model = AutoModelForCausalLM.from_pretrained("TsinghuaAI/CPM-Generate") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TsinghuaAI/CPM-Generate with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TsinghuaAI/CPM-Generate" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TsinghuaAI/CPM-Generate", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TsinghuaAI/CPM-Generate
- SGLang
How to use TsinghuaAI/CPM-Generate 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 "TsinghuaAI/CPM-Generate" \ --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": "TsinghuaAI/CPM-Generate", "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 "TsinghuaAI/CPM-Generate" \ --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": "TsinghuaAI/CPM-Generate", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TsinghuaAI/CPM-Generate with Docker Model Runner:
docker model run hf.co/TsinghuaAI/CPM-Generate
Canwen Xu commited on
Commit ·
73ef9bd
1
Parent(s): ce1c7c6
Update README.md
Browse files
README.md
CHANGED
|
@@ -29,7 +29,7 @@ text_generator('清华大学', max_length=50, do_sample=True, top_p=0.9)
|
|
| 29 |
|
| 30 |
#### Limitations and bias
|
| 31 |
|
| 32 |
-
The text generated by CPM is automatically generated by a neural network model trained on a large number of texts, which does not represent
|
| 33 |
|
| 34 |
## Training data
|
| 35 |
|
|
|
|
| 29 |
|
| 30 |
#### Limitations and bias
|
| 31 |
|
| 32 |
+
The text generated by CPM is automatically generated by a neural network model trained on a large number of texts, which does not represent the authors' or their institutes' official attitudes and preferences. The text generated by CPM is only used for technical and scientific purposes. If it infringes on your rights and interests or violates social morality, please do not propagate it, but contact the authors and the authors will deal with it promptly.
|
| 33 |
|
| 34 |
## Training data
|
| 35 |
|