Text Generation
Transformers
PyTorch
TensorBoard
gpt2
Generated from Trainer
custom_code
text-generation-inference
Instructions to use mrm8488/santacoder-finetuned-the-stack-rust with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/santacoder-finetuned-the-stack-rust with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mrm8488/santacoder-finetuned-the-stack-rust", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/santacoder-finetuned-the-stack-rust", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("mrm8488/santacoder-finetuned-the-stack-rust", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use mrm8488/santacoder-finetuned-the-stack-rust with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "mrm8488/santacoder-finetuned-the-stack-rust" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mrm8488/santacoder-finetuned-the-stack-rust", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mrm8488/santacoder-finetuned-the-stack-rust
- SGLang
How to use mrm8488/santacoder-finetuned-the-stack-rust 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 "mrm8488/santacoder-finetuned-the-stack-rust" \ --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": "mrm8488/santacoder-finetuned-the-stack-rust", "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 "mrm8488/santacoder-finetuned-the-stack-rust" \ --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": "mrm8488/santacoder-finetuned-the-stack-rust", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mrm8488/santacoder-finetuned-the-stack-rust with Docker Model Runner:
docker model run hf.co/mrm8488/santacoder-finetuned-the-stack-rust
| timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region | |
| 2023-02-10T15:04:24,119d4d67-7cbd-4cca-8fd0-42fbd67043cb,codecarbon,3452.725793838501,0.20740063958016539,0.34772163928723976,Spain,ESP,murcia,N,, | |
| 2023-02-11T18:16:27,f73eaa81-5d71-4008-aadb-910647cc8aad,codecarbon,8.042787790298462,0.0004746449971879528,0.00079577544618848,Spain,ESP,andalusia,N,, | |