Instructions to use inferenceport-ai/madlad400-10b-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inferenceport-ai/madlad400-10b-mt with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="inferenceport-ai/madlad400-10b-mt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("inferenceport-ai/madlad400-10b-mt") model = AutoModelForSeq2SeqLM.from_pretrained("inferenceport-ai/madlad400-10b-mt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00004-of-00009.safetensors from inferenceport-ai/madlad400-10b-mt: direct link, hf CLI and curl.
- Browser
- Download file 4.97 GB
-
https://huggingface.co/inferenceport-ai/madlad400-10b-mt/resolve/main/model-00004-of-00009.safetensors
- Command line
-
hf download hf://inferenceport-ai/madlad400-10b-mt/model-00004-of-00009.safetensors
-
curl -L -o model-00004-of-00009.safetensors https://huggingface.co/inferenceport-ai/madlad400-10b-mt/resolve/main/model-00004-of-00009.safetensors
4.97 GB
- Xet hash:
- 86ae1e9796378d570e587cc2f54c63c36b51228bd153991f3f2444cd61111031
- Size of remote file:
- 4.97 GB
- SHA256:
- 229207583daae9ed3282f0cfb467d366cb803417baad32865b9a735bafafceab
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