Instructions to use senseable/33x-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use senseable/33x-coder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="senseable/33x-coder")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("senseable/33x-coder") model = AutoModelForCausalLM.from_pretrained("senseable/33x-coder") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use senseable/33x-coder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "senseable/33x-coder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "senseable/33x-coder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/senseable/33x-coder
- SGLang
How to use senseable/33x-coder 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 "senseable/33x-coder" \ --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": "senseable/33x-coder", "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 "senseable/33x-coder" \ --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": "senseable/33x-coder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use senseable/33x-coder with Docker Model Runner:
docker model run hf.co/senseable/33x-coder
Humaneval score?
What are the coding benchmark scores? Humaneval and humaneval+
Id like to ask the bloke to quantize this model but I wanna see if its even worth it considering this is llama based, and llama generally doesnt do that well in coding unless finetuned correctly. But if you can surprise me with good coding benchmark scores Ill ask
I just realized the base model is deepseekcoder, but I would still like to see how much the model improved with another humaneval bench after your finetune
Human Eval is now in progress.
I've quantized it 5-bit with GGUF already if you want to test that out
senseable/33x-coder-gguf
thank you, im actually testing it right now