Instructions to use oobabooga/CodeBooga-34B-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oobabooga/CodeBooga-34B-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="oobabooga/CodeBooga-34B-v0.1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("oobabooga/CodeBooga-34B-v0.1") model = AutoModelForCausalLM.from_pretrained("oobabooga/CodeBooga-34B-v0.1") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use oobabooga/CodeBooga-34B-v0.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "oobabooga/CodeBooga-34B-v0.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "oobabooga/CodeBooga-34B-v0.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/oobabooga/CodeBooga-34B-v0.1
- SGLang
How to use oobabooga/CodeBooga-34B-v0.1 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 "oobabooga/CodeBooga-34B-v0.1" \ --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": "oobabooga/CodeBooga-34B-v0.1", "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 "oobabooga/CodeBooga-34B-v0.1" \ --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": "oobabooga/CodeBooga-34B-v0.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use oobabooga/CodeBooga-34B-v0.1 with Docker Model Runner:
docker model run hf.co/oobabooga/CodeBooga-34B-v0.1
Human eval results?
#2
by rombodawg - opened
Are we able to get this model evaluated on humaneval? So we can compare the scores to the models that were used in the merge
My anecdote is that it's way better than wizardcoder.
My anecdote is that it's way better than wizardcoder.
the little bit of testing i have done so far, agrees with that. ( for python at least. my only use case for AI )
I've been trying to code with C# and Forms/.Net, and it does a better job with it than pretty much every other model I've tried.