Instructions to use roshan151/Model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roshan151/Model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="roshan151/Model_output")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("roshan151/Model_output") model = AutoModelForMaskedLM.from_pretrained("roshan151/Model_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ad9f2c4d09f3b66557cc8b9addef542443e21ae93178f9126e35d2c3b570f87
- Size of remote file:
- 534 MB
- SHA256:
- 4c5b25cc6210669f1306cc873589308456bf2de3e5627bf780297aa2a402c630
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