Instructions to use harpertoken/chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harpertoken/chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="harpertoken/chat")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("harpertoken/chat") model = AutoModelForCausalLM.from_pretrained("harpertoken/chat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use harpertoken/chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "harpertoken/chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "harpertoken/chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/harpertoken/chat
- SGLang
How to use harpertoken/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 "harpertoken/chat" \ --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": "harpertoken/chat", "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 "harpertoken/chat" \ --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": "harpertoken/chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use harpertoken/chat with Docker Model Runner:
docker model run hf.co/harpertoken/chat
bniladridas commited on
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Parent(s): 19d9673
Add Related Models and Model Differences sections for truthful discussion
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README.md
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Interact with the API via the browser at:
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[http://localhost:8000/docs#/default/generate_response_chat_post](http://localhost:8000/docs#/default/generate_response_chat_post)
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Interact with the API via the browser at:
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[http://localhost:8000/docs#/default/generate_response_chat_post](http://localhost:8000/docs#/default/generate_response_chat_post)
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## Related Models
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- **harpertokenConvAI**: [https://huggingface.co/harpertoken/harpertokenConvAI](https://huggingface.co/harpertoken/harpertokenConvAI) - DistilBERT-based model for question answering. Note: This is not the base model for harpertokenConvFT due to incompatible architectures (DistilBERT vs GPT-2).
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- **Base Model**: This model is fine-tuned from GPT-2 ([openai/gpt2](https://huggingface.co/gpt2)).
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## Model Differences
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harpertokenConvFT is a GPT-2 model for conversational AI, while harpertokenConvAI is a DistilBERT model for question answering. They have different architectures, tokenizers, and parameters, making fine-tuning between them impossible. For truthful info, refer to the config.json files.
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