Instructions to use casperhansen/yi-6b-awq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use casperhansen/yi-6b-awq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="casperhansen/yi-6b-awq", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("casperhansen/yi-6b-awq", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use casperhansen/yi-6b-awq with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "casperhansen/yi-6b-awq" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "casperhansen/yi-6b-awq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/casperhansen/yi-6b-awq
- SGLang
How to use casperhansen/yi-6b-awq 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 "casperhansen/yi-6b-awq" \ --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": "casperhansen/yi-6b-awq", "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 "casperhansen/yi-6b-awq" \ --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": "casperhansen/yi-6b-awq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use casperhansen/yi-6b-awq with Docker Model Runner:
docker model run hf.co/casperhansen/yi-6b-awq
| { | |
| "_name_or_path": "/root/.cache/huggingface/hub/models--01-ai--Yi-6B/snapshots/07487978175a5047e71c8ab0228ddf641a5252ff", | |
| "architectures": [ | |
| "YiForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_yi.YiConfig", | |
| "AutoModel": "modeling_yi.YiModel", | |
| "AutoModelForCausalLM": "modeling_yi.YiForCausalLM" | |
| }, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 11008, | |
| "max_position_embeddings": 4096, | |
| "model_type": "Yi", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 4, | |
| "pad_token_id": 0, | |
| "quantization_config": { | |
| "bits": 4, | |
| "group_size": 128, | |
| "quant_method": "awq", | |
| "version": "gemm", | |
| "zero_point": true | |
| }, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 5000000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.35.0", | |
| "use_cache": true, | |
| "vocab_size": 64000 | |
| } | |