Text Generation
Transformers
Safetensors
interpgpt
interpretability
mechanistic-interpretability
task-decomposition
small-language-model
transformer-lens
custom_code
Instructions to use connaaa/interpgpt-adhd-23M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connaaa/interpgpt-adhd-23M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="connaaa/interpgpt-adhd-23M", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("connaaa/interpgpt-adhd-23M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use connaaa/interpgpt-adhd-23M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "connaaa/interpgpt-adhd-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-adhd-23M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/connaaa/interpgpt-adhd-23M
- SGLang
How to use connaaa/interpgpt-adhd-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-adhd-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-adhd-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-adhd-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-adhd-23M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use connaaa/interpgpt-adhd-23M with Docker Model Runner:
docker model run hf.co/connaaa/interpgpt-adhd-23M
File size: 765 Bytes
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"vocab_size": 8197,
"max_seq_len": 512,
"n_layers": 6,
"n_heads": 8,
"d_model": 512,
"d_ff": 2048,
"dropout": 0.25,
"pad_id": 8196,
"bias": false,
"variant": "adhd",
"transformers_version": "5.5.4",
"architectures": null,
"output_hidden_states": false,
"return_dict": true,
"dtype": null,
"chunk_size_feed_forward": 0,
"is_encoder_decoder": false,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1"
},
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1
},
"problem_type": null,
"_name_or_path": "",
"pad_token_id": 8196,
"auto_map": {
"AutoConfig": "configuration_interpgpt.InterpGPTConfig",
"AutoModel": "modeling_interpgpt.InterpGPTModel"
},
"model_type": "interpgpt",
"output_attentions": false
} |