Instructions to use joaoluislins/checkpoint-6620 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joaoluislins/checkpoint-6620 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="joaoluislins/checkpoint-6620")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("joaoluislins/checkpoint-6620") model = AutoModel.from_pretrained("joaoluislins/checkpoint-6620", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 825017e83b54faf2aa98af2343302718829d2a6645d6856fceadc62e7b591837
- Size of remote file:
- 565 MB
- SHA256:
- 42fede472ceed9148ac01d16eef195ec3c1a8ab9cdaadcbe8e94da7c81708fcf
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