Instructions to use goldfish-models/ibo_latn_full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use goldfish-models/ibo_latn_full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="goldfish-models/ibo_latn_full")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("goldfish-models/ibo_latn_full") model = AutoModelForCausalLM.from_pretrained("goldfish-models/ibo_latn_full", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use goldfish-models/ibo_latn_full with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "goldfish-models/ibo_latn_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/ibo_latn_full", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/goldfish-models/ibo_latn_full
- SGLang
How to use goldfish-models/ibo_latn_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/ibo_latn_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/ibo_latn_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/ibo_latn_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/ibo_latn_full", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use goldfish-models/ibo_latn_full with Docker Model Runner:
docker model run hf.co/goldfish-models/ibo_latn_full
Download pytorch_model.bin from goldfish-models/ibo_latn_full: direct link, hf CLI and curl.
- Browser
- Download file 502 MB
-
https://huggingface.co/goldfish-models/ibo_latn_full/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://goldfish-models/ibo_latn_full/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/goldfish-models/ibo_latn_full/resolve/main/pytorch_model.bin
502 MB
- Xet hash:
- 9a88d332ea1ce5864b3414fe2d3ca850f085ff91008e183c8b4a78a9f14a7c09
- Size of remote file:
- 502 MB
- SHA256:
- 513155b9eb76620f97650ec1454bc65c226e917cfe883011855a973ec1410702
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