Text Generation
Transformers
Safetensors
interpgpt
interpretability
mechanistic-interpretability
task-decomposition
small-language-model
transformer-lens
custom_code
Instructions to use connaaa/interpgpt-standard-23M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connaaa/interpgpt-standard-23M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="connaaa/interpgpt-standard-23M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("connaaa/interpgpt-standard-23M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use connaaa/interpgpt-standard-23M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "connaaa/interpgpt-standard-23M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "connaaa/interpgpt-standard-23M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/connaaa/interpgpt-standard-23M
- SGLang
How to use connaaa/interpgpt-standard-23M 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 "connaaa/interpgpt-standard-23M" \ --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": "connaaa/interpgpt-standard-23M", "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 "connaaa/interpgpt-standard-23M" \ --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": "connaaa/interpgpt-standard-23M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use connaaa/interpgpt-standard-23M with Docker Model Runner:
docker model run hf.co/connaaa/interpgpt-standard-23M
- Xet hash:
- 5b6d3af6d1158b8f93cf481013fd7635008b97140e77b6a41553cf94962067dc
- Size of remote file:
- 101 MB
- SHA256:
- 2cdcf5277237808f7ed6e4ae712d58dbef6b8ed0ba113a789c26dcdc4743067f
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