Text Generation
Transformers
Safetensors
English
tinybuddy
tiny-lm
tinystories
educational
built-with-llama
custom_code
Instructions to use Eeppa/TinyBuddy-30M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eeppa/TinyBuddy-30M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Eeppa/TinyBuddy-30M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Eeppa/TinyBuddy-30M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Eeppa/TinyBuddy-30M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Eeppa/TinyBuddy-30M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Eeppa/TinyBuddy-30M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Eeppa/TinyBuddy-30M
- SGLang
How to use Eeppa/TinyBuddy-30M 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 "Eeppa/TinyBuddy-30M" \ --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": "Eeppa/TinyBuddy-30M", "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 "Eeppa/TinyBuddy-30M" \ --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": "Eeppa/TinyBuddy-30M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Eeppa/TinyBuddy-30M with Docker Model Runner:
docker model run hf.co/Eeppa/TinyBuddy-30M
Commit History
-
Update modeling_tinybuddy.py
Verified signature4aba285 -
Update config.json
Verified signature6e74e54 -
Update config.json
Verified signature8c47c8b -
Delete configuration_tinybuddy.py
Verified signatureeeff2ff -
Update modeling_tinybuddy.py
Verified signature0247f2b -
Update modeling_tinybuddy.py
Verified signature4954ba4 -
Update modeling_tinybuddy.py
Verified signaturea6e1f03 -
Update modeling_tinybuddy.py
Verified signaturef2c7fb0 -
Update configuration_tinybuddy.py
Verified signature0afbae0 -
Update config.json
Verified signature23a5917 -
Upload 12 files
Verified signature06513db -
Delete __init__.py
Verified signature5dc55c1 -
Delete tokenizer.json
Verified signature6fabde8 -
Delete Model.py
Verified signature0c7fa77 -
Create __init__.py
Verified signature1bc6acb -
Upload tokenizer.json
Verified signature48b5ab0 -
Update Model.py
Verified signaturebdce3c5 -
Delete README.md
Verified signature59e2c62 -
Create README.txt
Verified signaturec360acf -
Update README.md
Verified signature9b9c2ab -
Create Model.py
Verified signature83154d1 -
initial commit
Verified signature261ebf5