Text Generation
Transformers
PyTorch
Safetensors
English
tiny_smart_llm
gpt
language-model
conversational
custom_code
Instructions to use HenrySentinel/tinyMind with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HenrySentinel/tinyMind with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="HenrySentinel/tinyMind", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("HenrySentinel/tinyMind", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use HenrySentinel/tinyMind with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HenrySentinel/tinyMind" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HenrySentinel/tinyMind", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/HenrySentinel/tinyMind
- SGLang
How to use HenrySentinel/tinyMind 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 "HenrySentinel/tinyMind" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HenrySentinel/tinyMind", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "HenrySentinel/tinyMind" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HenrySentinel/tinyMind", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use HenrySentinel/tinyMind with Docker Model Runner:
docker model run hf.co/HenrySentinel/tinyMind
Upload config.json with huggingface_hub
Browse files- config.json +14 -0
config.json
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{
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"architectures": [
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"TinySmartLLMForHF"
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],
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"dropout": 0.1,
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"max_seq_len": 512,
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"model_type": "tiny_smart_llm",
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"n_embd": 256,
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"n_heads": 8,
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"n_layers": 6,
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"torch_dtype": "float32",
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"transformers_version": "4.51.3",
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"vocab_size": 50257
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}
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