Instructions to use openchat/openchat_v3.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openchat/openchat_v3.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openchat/openchat_v3.2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("openchat/openchat_v3.2") model = AutoModelForCausalLM.from_pretrained("openchat/openchat_v3.2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use openchat/openchat_v3.2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openchat/openchat_v3.2" # 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_v3.2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/openchat/openchat_v3.2
- SGLang
How to use openchat/openchat_v3.2 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_v3.2" \ --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_v3.2", "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_v3.2" \ --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_v3.2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use openchat/openchat_v3.2 with Docker Model Runner:
docker model run hf.co/openchat/openchat_v3.2
How is the coding performance?
Does the coding performance compare to gpt-3.5 as in chatgpt? Is it far bellow that? Also can you share what all coding data you trained the model on?
It is lower than gpt-3.5 in terms of encoding. Llama 2 was likely trained on very little encoded data. Also, all data can be found at https://huggingface.co/datasets/openchat/openchat_sharegpt_v3
It is lower than gpt-3.5 in terms of encoding. Llama 2 was likely trained on very little encoded data. Also, all data can be found at https://huggingface.co/datasets/openchat/openchat3_orca_dataset
The link is not working
Sorry, typo, fixed now