Instructions to use SupraLabs/Supra-Router-51M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SupraLabs/Supra-Router-51M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SupraLabs/Supra-Router-51M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SupraLabs/Supra-Router-51M") model = AutoModelForCausalLM.from_pretrained("SupraLabs/Supra-Router-51M") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SupraLabs/Supra-Router-51M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SupraLabs/Supra-Router-51M" # 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-Router-51M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SupraLabs/Supra-Router-51M
- SGLang
How to use SupraLabs/Supra-Router-51M 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-Router-51M" \ --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-Router-51M", "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-Router-51M" \ --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-Router-51M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SupraLabs/Supra-Router-51M with Docker Model Runner:
docker model run hf.co/SupraLabs/Supra-Router-51M
Idea do modelo
Por favor, crie um modelo Supra-50M em português, chamado: Supra-50M-Portugues-Base (e Instruct), treinado em GigaVerbo, FineWeb2 e Wikipédia.
Vou pesquisar dados em portugues pra fazer
Espere um segundo, você vai usar CPT, finetune ou pré-treinar do zero?
Todos os modelos da Supra são treinados do zero por nós!
E sim! Estamos trabalhando para tornar nossos modelos multilíngues. Por exemplo:
- Inglês–Francês
- Inglês–Português
- Inglês–Japonês
E muitos outros...
Vamos construir tudo isso sobre os nossos modelos Supra-2 Base e disponibilizar os checkpoints como código aberto (open source) ❤️
QyrouNnet-AI, please, somehow add the Russian language to the models ❤️
Certo, mas qual conjunto de dados você vai usar?
Nós faremos o nosso próprio, e usaremos dados públicos de várias fontes com uma licença de código aberto.
Obrigado/a!
@MishaGGG We are happy to look into this! Right now, our entire team is fully focused on the development of the SupraCode and Supra-2 models. However, we do plan to expand the upcoming Supra-2 models to support multiple languages. This process will take some time, so we truly appreciate your patience and support.