Instructions to use benjaminsul/fine_tuned_he_to_tanach with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjaminsul/fine_tuned_he_to_tanach 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="benjaminsul/fine_tuned_he_to_tanach")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("benjaminsul/fine_tuned_he_to_tanach") model = AutoModelForSeq2SeqLM.from_pretrained("benjaminsul/fine_tuned_he_to_tanach", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b68a24633e94b75e90104c5771c02a9b6a03690e30a90d0fa482dc4b2894ec0e
- Size of remote file:
- 5.3 kB
- SHA256:
- 64a63885ad441bdce019849dcc702b82d8df04a920ce0838da2822899e343c17
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