Instructions to use HenrySentinel/tinyMind-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HenrySentinel/tinyMind-SFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="HenrySentinel/tinyMind-SFT") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("HenrySentinel/tinyMind-SFT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use HenrySentinel/tinyMind-SFT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HenrySentinel/tinyMind-SFT" # 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-SFT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/HenrySentinel/tinyMind-SFT
- SGLang
How to use HenrySentinel/tinyMind-SFT 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-SFT" \ --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-SFT", "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-SFT" \ --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-SFT", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use HenrySentinel/tinyMind-SFT with Docker Model Runner:
docker model run hf.co/HenrySentinel/tinyMind-SFT
| { | |
| "architectures": [ | |
| "TinyMindForCausalLM" | |
| ], | |
| "bos_token_id": 50256, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "eos_token_id": 50256, | |
| "hidden_size": 256, | |
| "max_position_embeddings": 512, | |
| "max_seq_len": 512, | |
| "model_type": "tiny_smart_llm", | |
| "n_embd": 256, | |
| "n_heads": 8, | |
| "n_layers": 6, | |
| "num_attention_heads": 8, | |
| "num_hidden_layers": 6, | |
| "pad_token_id": 50256, | |
| "transformers_version": "5.6.2", | |
| "use_cache": false, | |
| "vocab_size": 50257 | |
| } | |