Text Generation
Transformers
Safetensors
llama
conversational
Eval Results
text-generation-inference
Instructions to use 01-ai/Yi-1.5-9B-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 01-ai/Yi-1.5-9B-Chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="01-ai/Yi-1.5-9B-Chat") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("01-ai/Yi-1.5-9B-Chat") model = AutoModelForCausalLM.from_pretrained("01-ai/Yi-1.5-9B-Chat", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use 01-ai/Yi-1.5-9B-Chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "01-ai/Yi-1.5-9B-Chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "01-ai/Yi-1.5-9B-Chat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/01-ai/Yi-1.5-9B-Chat
- SGLang
How to use 01-ai/Yi-1.5-9B-Chat 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 "01-ai/Yi-1.5-9B-Chat" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "01-ai/Yi-1.5-9B-Chat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "01-ai/Yi-1.5-9B-Chat" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "01-ai/Yi-1.5-9B-Chat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use 01-ai/Yi-1.5-9B-Chat with Docker Model Runner:
docker model run hf.co/01-ai/Yi-1.5-9B-Chat
| 076b120baa027eee3ffcecb9bd2243f0 config.json | |
| cc8e8e96be047d8884a430c2ba535801 generation_config.json | |
| a4bd326c13fb1f27b7145dffffe2f421 model-00001-of-00004.safetensors | |
| 054231cb22dc430b9e3424a4c5a361d6 model-00002-of-00004.safetensors | |
| 1cd9fd99d24ce8c8f557decb08e73776 model-00003-of-00004.safetensors | |
| 1e9be95036261e6c214e5ab5fe50194f model-00004-of-00004.safetensors | |
| 8918290652a4ee6dc89dea20d86768d4 model.safetensors.index.json | |
| ca53c07de6656e16e23f2665679d7ce3 special_tokens_map.json | |
| 291724ef50f729e45d68f474a7755bbc tokenizer.model | |
| 366d56972635d94369dd6e57e90d1e4a tokenizer_config.json | |