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)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Eeppa/TinyBuddy-30M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- 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
Update configuration_tinybuddy.py
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configuration_tinybuddy.py
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Configuration class for TinyBuddy-30M.
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Configuration class for TinyBuddy-30M.
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"""
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from transformers import PretrainedConfig
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class GPTConfig(PretrainedConfig):
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model_type = "tinybuddy"
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def __init__(
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self,
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vocab_size: int = 50000,
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block_size: int = 512,
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n_layer: int = 6,
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n_head: int = 8,
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n_embd: int = 256,
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mlp_ratio: int = 4,
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dropout: float = 0.0,
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tie_weights: bool = False,
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**kwargs
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):
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super().__init__(**kwargs)
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self.vocab_size = vocab_size
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self.block_size = block_size
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self.n_layer = n_layer
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self.n_head = n_head
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self.n_embd = n_embd
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self.mlp_ratio = mlp_ratio
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self.dropout = dropout
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self.tie_weights = tie_weights
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