Text Generation
Transformers
Safetensors
llama
trl
sft
Generated from Trainer
text-generation-inference
Instructions to use stojchet/jd3-jsft8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stojchet/jd3-jsft8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="stojchet/jd3-jsft8")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("stojchet/jd3-jsft8") model = AutoModelForCausalLM.from_pretrained("stojchet/jd3-jsft8") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use stojchet/jd3-jsft8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "stojchet/jd3-jsft8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stojchet/jd3-jsft8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/stojchet/jd3-jsft8
- SGLang
How to use stojchet/jd3-jsft8 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 "stojchet/jd3-jsft8" \ --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": "stojchet/jd3-jsft8", "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 "stojchet/jd3-jsft8" \ --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": "stojchet/jd3-jsft8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use stojchet/jd3-jsft8 with Docker Model Runner:
docker model run hf.co/stojchet/jd3-jsft8
Upload params.json with huggingface_hub
Browse files- params.json +1 -0
params.json
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{"max_seq_length": 1000, "language": "java", "dataset_size": 5000, "epochs": 3, "per_device_train_batch_size": 8, "gradient_accumulation_steps": 16, "weight_decay": 0.1, "learning_rate": 5e-05, "no_lora": true, "lora_r": 64, "lora_alpha": 16, "lora_dropout": 0.1, "dataset_name": "stojchet/csn_java_python_subset", "base_model": "deepseek-ai/deepseek-coder-1.3b-base", "dataset_ref_field": "whole_func_string"}
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