Text Generation
Transformers
Safetensors
llama
trl
dpo
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use noza-kit/JP3_ACbase_byGemini_2-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use noza-kit/JP3_ACbase_byGemini_2-adapter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="noza-kit/JP3_ACbase_byGemini_2-adapter")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("noza-kit/JP3_ACbase_byGemini_2-adapter") model = AutoModelForCausalLM.from_pretrained("noza-kit/JP3_ACbase_byGemini_2-adapter") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use noza-kit/JP3_ACbase_byGemini_2-adapter with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "noza-kit/JP3_ACbase_byGemini_2-adapter" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "noza-kit/JP3_ACbase_byGemini_2-adapter", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/noza-kit/JP3_ACbase_byGemini_2-adapter
- SGLang
How to use noza-kit/JP3_ACbase_byGemini_2-adapter 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 "noza-kit/JP3_ACbase_byGemini_2-adapter" \ --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": "noza-kit/JP3_ACbase_byGemini_2-adapter", "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 "noza-kit/JP3_ACbase_byGemini_2-adapter" \ --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": "noza-kit/JP3_ACbase_byGemini_2-adapter", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use noza-kit/JP3_ACbase_byGemini_2-adapter with Docker Model Runner:
docker model run hf.co/noza-kit/JP3_ACbase_byGemini_2-adapter
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "transformers_version": "4.52.3" | |
| } | |