Instructions to use goldfish-models/snd_arab_full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use goldfish-models/snd_arab_full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="goldfish-models/snd_arab_full")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("goldfish-models/snd_arab_full") model = AutoModelForCausalLM.from_pretrained("goldfish-models/snd_arab_full") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use goldfish-models/snd_arab_full with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "goldfish-models/snd_arab_full" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "goldfish-models/snd_arab_full", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/goldfish-models/snd_arab_full
- SGLang
How to use goldfish-models/snd_arab_full 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 "goldfish-models/snd_arab_full" \ --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": "goldfish-models/snd_arab_full", "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 "goldfish-models/snd_arab_full" \ --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": "goldfish-models/snd_arab_full", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use goldfish-models/snd_arab_full with Docker Model Runner:
docker model run hf.co/goldfish-models/snd_arab_full
- Xet hash:
- f4c24eefcf5dfc5f2bcfaccf722d25b43a02a45f3b48291541c4b21d730ef7ea
- Size of remote file:
- 502 MB
- SHA256:
- 03c715e0d555d2128edd7aa816d9d64ccc56601d8f9ba1c2247843cb2c4eba27
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