Text Generation
Transformers
Safetensors
English
llama
tinystories
language-model
educational
text-generation-inference
Instructions to use manojredhat/tiny-llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manojredhat/tiny-llama with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="manojredhat/tiny-llama")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("manojredhat/tiny-llama") model = AutoModelForCausalLM.from_pretrained("manojredhat/tiny-llama") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use manojredhat/tiny-llama with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "manojredhat/tiny-llama" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "manojredhat/tiny-llama", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/manojredhat/tiny-llama
- SGLang
How to use manojredhat/tiny-llama 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 "manojredhat/tiny-llama" \ --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": "manojredhat/tiny-llama", "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 "manojredhat/tiny-llama" \ --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": "manojredhat/tiny-llama", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use manojredhat/tiny-llama with Docker Model Runner:
docker model run hf.co/manojredhat/tiny-llama
Add YAML metadata to README for proper model card display
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README.md
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# Tiny LLaMA - TinyStories Edition
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A lightweight LLaMA-2 inspired model trained on the TinyStories dataset. This model is designed for educational purposes and lightweight inference.
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---
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library_name: transformers
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license: apache-2.0
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language:
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- en
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tags:
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- tinystories
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- llama
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- language-model
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- educational
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- safetensors
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datasets:
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- roneneldan/TinyStories
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model-index:
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- name: Tiny LLaMA
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results: []
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---
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# Tiny LLaMA - TinyStories Edition
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A lightweight LLaMA-2 inspired model trained on the TinyStories dataset. This model is designed for educational purposes and lightweight inference.
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