Text Generation
Transformers
Safetensors
PyTorch
English
tiny
tinyllm
transformer
causal-lm
tinystories
storytelling
small-language-model
from-scratch
custom_code
Instructions to use Krishna0812/Tiny_Stories with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Krishna0812/Tiny_Stories with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Krishna0812/Tiny_Stories", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Krishna0812/Tiny_Stories", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Krishna0812/Tiny_Stories with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Krishna0812/Tiny_Stories" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Krishna0812/Tiny_Stories", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Krishna0812/Tiny_Stories
- SGLang
How to use Krishna0812/Tiny_Stories 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 "Krishna0812/Tiny_Stories" \ --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": "Krishna0812/Tiny_Stories", "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 "Krishna0812/Tiny_Stories" \ --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": "Krishna0812/Tiny_Stories", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Krishna0812/Tiny_Stories with Docker Model Runner:
docker model run hf.co/Krishna0812/Tiny_Stories
- Xet hash:
- 4f612c81cc212e0af558cc2375ea76e7b1f0c31919301ccb56a28fcdf2e6d572
- Size of remote file:
- 371 kB
- SHA256:
- 4cffac9db68a0db7daf412a3811d5731bef8c323414e638ba0480d9980128453
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