Text Generation
Transformers
PyTorch
TensorBoard
code
gpt2
Generated from Trainer
clojure
codegen
custom_code
text-generation-inference
Instructions to use mrm8488/santacoder-finetuned-the-stack-clojure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/santacoder-finetuned-the-stack-clojure with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="mrm8488/santacoder-finetuned-the-stack-clojure", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/santacoder-finetuned-the-stack-clojure", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("mrm8488/santacoder-finetuned-the-stack-clojure", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use mrm8488/santacoder-finetuned-the-stack-clojure 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-clojure" # 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-clojure", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/mrm8488/santacoder-finetuned-the-stack-clojure
- SGLang
How to use mrm8488/santacoder-finetuned-the-stack-clojure 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-clojure" \ --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-clojure", "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-clojure" \ --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-clojure", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use mrm8488/santacoder-finetuned-the-stack-clojure with Docker Model Runner:
docker model run hf.co/mrm8488/santacoder-finetuned-the-stack-clojure
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<|endoftext|>", | |
| "eos_token": "<|endoftext|>", | |
| "errors": "replace", | |
| "model_max_length": 2048, | |
| "name_or_path": "bigcode/santacoder", | |
| "special_tokens_map_file": "/root/.cache/huggingface/hub/models--bigcode--santacoder/snapshots/636ad0a694975c25bdb8a16fb8ffda275525a2a8/special_tokens_map.json", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |