Text Generation
Transformers
Safetensors
English
llama
small
cpu
supra
tiny
mini
open
open-source
Eval Results (legacy)
text-generation-inference
Instructions to use SupraLabs/Supra-Mini-0.1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SupraLabs/Supra-Mini-0.1M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SupraLabs/Supra-Mini-0.1M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SupraLabs/Supra-Mini-0.1M") model = AutoModelForCausalLM.from_pretrained("SupraLabs/Supra-Mini-0.1M") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SupraLabs/Supra-Mini-0.1M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SupraLabs/Supra-Mini-0.1M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SupraLabs/Supra-Mini-0.1M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SupraLabs/Supra-Mini-0.1M
- SGLang
How to use SupraLabs/Supra-Mini-0.1M 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 "SupraLabs/Supra-Mini-0.1M" \ --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": "SupraLabs/Supra-Mini-0.1M", "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 "SupraLabs/Supra-Mini-0.1M" \ --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": "SupraLabs/Supra-Mini-0.1M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SupraLabs/Supra-Mini-0.1M with Docker Model Runner:
docker model run hf.co/SupraLabs/Supra-Mini-0.1M
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---
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# 🦅 Supra Mini 0.1M
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metrics: null
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model-index:
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- name: WikiText
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results:
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- task:
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type: text-generation
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dataset:
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name: wikipedia
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type: wikitext
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metrics:
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- name: WikiText
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type: WikiText
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value: 25.16(2500%)
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source:
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name: Self-eval
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url: https://huggingface.co/SupraLabs/Supra-Mini-0.1M
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- name: Blimp
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results:
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- task:
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type: text-generation
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dataset:
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name: Blimp
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type: BLiMP
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metrics:
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- name: BLIMP
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type: BLIMP
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value: 0.5(50%)
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source:
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name: Self-eval
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url: https://huggingface.co/SupraLabs/Supra-Mini-0.1M
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new_version: SupraLabs/Supra-Mini-v2-0.1M
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---
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# 🦅 Supra Mini 0.1M
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