Instructions to use Smilyai-labs/CodVa-1-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Smilyai-labs/CodVa-1-Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Smilyai-labs/CodVa-1-Small", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Smilyai-labs/CodVa-1-Small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Smilyai-labs/CodVa-1-Small with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Smilyai-labs/CodVa-1-Small" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Smilyai-labs/CodVa-1-Small", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Smilyai-labs/CodVa-1-Small
- SGLang
How to use Smilyai-labs/CodVa-1-Small 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 "Smilyai-labs/CodVa-1-Small" \ --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": "Smilyai-labs/CodVa-1-Small", "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 "Smilyai-labs/CodVa-1-Small" \ --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": "Smilyai-labs/CodVa-1-Small", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Smilyai-labs/CodVa-1-Small with Docker Model Runner:
docker model run hf.co/Smilyai-labs/CodVa-1-Small
New Model!
You've got great timing. I was just looking for something to do. I need a model to run my SAE weight trainer I'm testing right now. Your model falls pretty well in the middle of the size I was looking for. Let me see what I can do. I think I could get this started without much adjustment.
Alright, I was a little over zealous on the capability of my SAE trainer. I thought MoE wouldn't be an issue, and I was alright until a certain point. Sorry for the late response I'm usually quicker than this. I'm just leaving a family reunion today so I was a bit preoccupied. I'll have a brain atlas with interpretation for you shortly here.