Text Generation
Transformers
PyTorch
Safetensors
English
gpt2
chemistry
biology
text-generation-inference
Instructions to use Arjun-G-Ravi/chat-GPT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arjun-G-Ravi/chat-GPT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Arjun-G-Ravi/chat-GPT2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Arjun-G-Ravi/chat-GPT2") model = AutoModelForCausalLM.from_pretrained("Arjun-G-Ravi/chat-GPT2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Arjun-G-Ravi/chat-GPT2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Arjun-G-Ravi/chat-GPT2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Arjun-G-Ravi/chat-GPT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Arjun-G-Ravi/chat-GPT2
- SGLang
How to use Arjun-G-Ravi/chat-GPT2 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 "Arjun-G-Ravi/chat-GPT2" \ --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": "Arjun-G-Ravi/chat-GPT2", "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 "Arjun-G-Ravi/chat-GPT2" \ --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": "Arjun-G-Ravi/chat-GPT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Arjun-G-Ravi/chat-GPT2 with Docker Model Runner:
docker model run hf.co/Arjun-G-Ravi/chat-GPT2
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This is a fine tuned version of OpenAI's GPT2, made to be good at chatting and question-answering. The model seems to be very good for a 124M parameter model in general knowledge.
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Intended purpose of the model: To create a powerful, easy to use and reliable model to be run on a consumer level graphics card (or maybe even a CPU).
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This model vastly outperforms GPT2 and many other similar parameter models.
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This is a fine tuned version of OpenAI's GPT2, made to be good at chatting and question-answering. The model seems to be very good for a 124M parameter model in general knowledge.
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Intended purpose of the model: To create a powerful, easy to use and reliable model to be run on a consumer level graphics card (or maybe even a CPU).
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This model vastly outperforms GPT2 and many other similar parameter models.
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For more details, visit: https://github.com/Arjun-G-Ravi/chat-GPT-2
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