Instructions to use nllg/detikzify-ds-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nllg/detikzify-ds-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nllg/detikzify-ds-7b")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("nllg/detikzify-ds-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nllg/detikzify-ds-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nllg/detikzify-ds-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nllg/detikzify-ds-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nllg/detikzify-ds-7b
- SGLang
How to use nllg/detikzify-ds-7b 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 "nllg/detikzify-ds-7b" \ --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": "nllg/detikzify-ds-7b", "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 "nllg/detikzify-ds-7b" \ --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": "nllg/detikzify-ds-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nllg/detikzify-ds-7b with Docker Model Runner:
docker model run hf.co/nllg/detikzify-ds-7b
Download generation_config.json from nllg/detikzify-ds-7b: direct link, hf CLI and curl.
- Browser
- Download file 147 Bytes
-
https://huggingface.co/nllg/detikzify-ds-7b/resolve/main/generation_config.json
- Command line
-
hf download hf://nllg/detikzify-ds-7b/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/nllg/detikzify-ds-7b/resolve/main/generation_config.json
147 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 100000, | |
| "eos_token_id": 100015, | |
| "pad_token_id": 100016, | |
| "transformers_version": "4.38.1" | |
| } | |