Instructions to use siliconcorerina/rina-coder-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use siliconcorerina/rina-coder-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="siliconcorerina/rina-coder-base")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("siliconcorerina/rina-coder-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use siliconcorerina/rina-coder-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "siliconcorerina/rina-coder-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "siliconcorerina/rina-coder-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/siliconcorerina/rina-coder-base
- SGLang
How to use siliconcorerina/rina-coder-base 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 "siliconcorerina/rina-coder-base" \ --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": "siliconcorerina/rina-coder-base", "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 "siliconcorerina/rina-coder-base" \ --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": "siliconcorerina/rina-coder-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use siliconcorerina/rina-coder-base with Docker Model Runner:
docker model run hf.co/siliconcorerina/rina-coder-base
| license: mit | |
| language: | |
| - en | |
| - fr | |
| - code | |
| library_name: transformers | |
| pipeline_tag: text-generation | |
| tags: | |
| - code | |
| - code-generation | |
| - rina-ai | |
| - llm | |
| # RINA Coder — Base | |
| > Modele de langage RINA AI dedie a la generation, la completion et l explication de code. | |
| > Site : [plateforme-rina.com](https://plateforme-rina.com) · Code : [github.com/siliconcorerina/RINA-AI](https://github.com/siliconcorerina/RINA-AI) | |
| **Statut : placeholder.** Les poids ne sont pas encore publies. Ce depot reserve l identifiant `siliconcorerina/rina-coder-base` et decrit le modele cible. La premiere version sera annoncee via les [issues du depot GitHub](https://github.com/siliconcorerina/RINA-AI/issues/4). | |
| ## Description | |
| RINA Coder est la famille de modeles de generation de code maintenue par l equipe RINA AI. Cette variante `base` est destinee a la completion et a la generation libre. Une variante `instruct` suivra pour les usages conversationnels. | |
| ## Usage prevu | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model_id = "siliconcorerina/rina-coder-base" | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto") | |
| prompt = "def fibonacci(n):" | |
| inputs = tokenizer(prompt, return_tensors="pt").to(model.device) | |
| outputs = model.generate(**inputs, max_new_tokens=128, temperature=0.2) | |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) | |
| ``` | |
| Voir aussi le script de demo : [demo/inference_example.py](https://github.com/siliconcorerina/RINA-AI/blob/main/demo/inference_example.py). | |
| ## Cas d usage | |
| - Completion de code dans des editeurs et IDE | |
| - Generation de fonctions a partir de docstrings | |
| - Explication de snippets de code | |
| - Refactoring assiste | |
| - Tests unitaires generes a partir du code source | |
| ## Hors perimetre | |
| - Conseil juridique, medical ou financier | |
| - Decisions impactant des personnes (recrutement, credit, etc.) | |
| - Usage en production sans verification humaine du code genere | |
| ## Donnees d entrainement | |
| A documenter lors de la publication du premier checkpoint. Les sources prevues incluent : | |
| - Code open source sous licences permissives | |
| - Documentation technique publique | |
| - Corpus de problemes de programmation (HumanEval-like) | |
| ## Evaluation | |
| Les benchmarks cibles sont : | |
| | Benchmark | Statut | | |
| |-----------|--------| | |
| | HumanEval (pass@1) | a venir | | |
| | MBPP (pass@1) | a venir | | |
| | MultiPL-E (Rust, Go, Kotlin) | a venir | | |
| | RINA-Bench (interne) | a venir | | |
| Suivi : [issues evaluation](https://github.com/siliconcorerina/RINA-AI/labels/evaluation). | |
| ## Limitations | |
| - Le code genere peut contenir des bugs, des failles de securite, ou ne pas compiler. Toujours relire et tester. | |
| - Le modele peut halluciner des API ou des bibliotheques inexistantes. | |
| - Les performances varient fortement selon le langage et le domaine. | |
| - Le contexte est limite ; les fichiers tres longs ne sont pas couverts dans une seule passe. | |
| ## Licence | |
| MIT. Voir [LICENSE](https://github.com/siliconcorerina/RINA-AI/blob/main/LICENSE). | |
| ## Contact | |
| - Site : [plateforme-rina.com](https://plateforme-rina.com) | |
| - Email : [hello@plateforme-rina.com](mailto:hello@plateforme-rina.com) | |
| - GitHub : [github.com/siliconcorerina](https://github.com/siliconcorerina) | |
| ## Citation | |
| ```bibtex | |
| @misc{rinacoder2026, | |
| title = {RINA Coder: a code language model by RINA AI}, | |
| author = {RINA AI Team}, | |
| year = {2026}, | |
| url = {https://huggingface.co/siliconcorerina/rina-coder-base} | |
| } | |
| ``` | |