Instructions to use hf-tiny-model-private/tiny-random-FSMTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FSMTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-FSMTModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FSMTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-FSMTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f533bc1a0109f73e6cd01412bd250ebd7801a77480db79d2ed9d06637ff43f5
- Size of remote file:
- 4.08 MB
- SHA256:
- 8dc59b3518a69ac953e14c64ac17c679d50ac1e58b7f84f4418636c0f6ce2565
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