Instructions to use openchat/openchat_v2_w with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openchat/openchat_v2_w with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openchat/openchat_v2_w")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("openchat/openchat_v2_w") model = AutoModelForCausalLM.from_pretrained("openchat/openchat_v2_w") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use openchat/openchat_v2_w with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openchat/openchat_v2_w" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openchat/openchat_v2_w", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/openchat/openchat_v2_w
- SGLang
How to use openchat/openchat_v2_w 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 "openchat/openchat_v2_w" \ --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": "openchat/openchat_v2_w", "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 "openchat/openchat_v2_w" \ --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": "openchat/openchat_v2_w", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use openchat/openchat_v2_w with Docker Model Runner:
docker model run hf.co/openchat/openchat_v2_w
Adding `safetensors` variant of this model
#6 opened over 1 year ago
by
SFconvertbot
Adding Evaluation Results
#5 opened over 2 years ago
by
leaderboard-pr-bot
Great work, but why only 2048 context length?
1
#4 opened almost 3 years ago
by
SamuelAzran
Size of model?
1
#3 opened almost 3 years ago
by
jurassicpark
HF Full Example
#2 opened almost 3 years ago
by
MK-CUPIST
Hello, can you elaborate on these conditional behavior cloning and weighted behavior cloning?
3
#1 opened almost 3 years ago
by
teknium