Instructions to use sadiqj/camlcoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sadiqj/camlcoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="sadiqj/camlcoder", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("sadiqj/camlcoder", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use sadiqj/camlcoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sadiqj/camlcoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sadiqj/camlcoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/sadiqj/camlcoder
- SGLang
How to use sadiqj/camlcoder 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 "sadiqj/camlcoder" \ --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": "sadiqj/camlcoder", "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 "sadiqj/camlcoder" \ --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": "sadiqj/camlcoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use sadiqj/camlcoder with Docker Model Runner:
docker model run hf.co/sadiqj/camlcoder
Update README.md
#1
by jonludlam - opened
README.md
CHANGED
|
@@ -15,7 +15,7 @@ programming_language:
|
|
| 15 |
# camlcoder
|
| 16 |
|
| 17 |
## Model Description
|
| 18 |
-
`camlcoder` is a 2.7B Causal Language Model focused on **Code Completion** for OCaml. It is a fine-tuned version of [replit-code-v1-3b](https://www.huggingface.
|
| 19 |
|
| 20 |
## License
|
| 21 |
The model checkpoint and vocabulary file are licensed under the Creative Commons license (CC BY-SA-4.0).
|
|
|
|
| 15 |
# camlcoder
|
| 16 |
|
| 17 |
## Model Description
|
| 18 |
+
`camlcoder` is a 2.7B Causal Language Model focused on **Code Completion** for OCaml. It is a fine-tuned version of [replit-code-v1-3b](https://www.huggingface.co/replit/replit-code-v1-3b). The model has been trained on a subset of the [Stack Dedup v1.2 dataset](https://arxiv.org/abs/2211.15533) and the most recent version of [all packages in Opam that compile on OCaml 5.0](https://www.huggingface.com/sadiqj/opam-source).
|
| 19 |
|
| 20 |
## License
|
| 21 |
The model checkpoint and vocabulary file are licensed under the Creative Commons license (CC BY-SA-4.0).
|