Instructions to use 0xideas/rustral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0xideas/rustral with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="0xideas/rustral")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("0xideas/rustral") model = AutoModelForCausalLM.from_pretrained("0xideas/rustral", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use 0xideas/rustral with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "0xideas/rustral" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "0xideas/rustral", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/0xideas/rustral
- SGLang
How to use 0xideas/rustral 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 "0xideas/rustral" \ --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": "0xideas/rustral", "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 "0xideas/rustral" \ --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": "0xideas/rustral", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use 0xideas/rustral with Docker Model Runner:
docker model run hf.co/0xideas/rustral
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Download README.md from 0xideas/rustral: direct link, hf CLI and curl.
- Browser
- Download file 2.41 kB
-
https://huggingface.co/0xideas/rustral/resolve/main/README.md
- Command line
-
hf download hf://0xideas/rustral/README.md
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curl -L -o README.md https://huggingface.co/0xideas/rustral/resolve/main/README.md
2.41 kB
| # For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1 | |
| # Doc / guide: https://huggingface.co/docs/hub/model-cards | |
| {{ card_data }} | |
| # Model Card for rustral-2-2k-2024-1-6 | |
| This is an instruction finetune of Mistral-7B-v0.1 on a custom dataset of Rust code snippets. The current version was finetuned on 2k examples for 3 epochs, with instructions being extracted from the comments of the code itself. Future versions will be based on more data and generated instructions. | |
| ## Model Details | |
| ### Model Description | |
| <!-- Provide a longer summary of what this model is. --> | |
| - **Developed by:** Leon Luithlen | |
| - **Model type:** Mistral-7B-v0.1 variant | |
| - **Language(s) (NLP):** Rust, English | |
| - **License:** apache-2.0 | |
| - **Finetuned from model [optional]:** Mistral-7B-v0.1 | |
| ## Uses | |
| This model is intended as a code assistant that develops short snippets, such as a single Rust struct or function, from the immediately preceding code and an instruction. | |
| ### Direct Use | |
| After compiling to the appropriate quantization size for your hardware with llama.cpp, it can be used like other Mistral-7B variants with the following input format: | |
| ``` | |
| Below is an instruction that describes a task, paired with an input that | |
| provides further context. Write a response that appropriately completes the | |
| request. | |
| ### Instruction: | |
| {instruction} | |
| ### Input: | |
| {up_to_two_previous_snippets} | |
| ### Response: | |
| ``` | |
| ### Out-of-Scope Use | |
| <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> | |
| Any programming language other than Rust, natural languages | |
| ## Bias, Risks, and Limitations | |
| <!-- This section is meant to convey both technical and sociotechnical limitations. --> | |
| Currently not evaluated systematically, as there is no agreed benchmark for code assistance tasks in Rust. | |
| For uses outside its intended scope, the model is likely to behave similarly to Mistral-7B, but probably worse. | |
| ### Recommendations | |
| <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> | |
| The same caveats that apply to Mistral-7B apply to this model as well. | |
| ## Training Details | |
| ### Training Data | |
| Training data is sourced from open source and permissively licensed Rust projects, but is not public. | |