Instructions to use improz4/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use improz4/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="improz4/model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("improz4/model") model = AutoModelForMaskedLM.from_pretrained("improz4/model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 246c0e28795f5ec16cafe274cb3f84c6239663f0d502fcd624e0b5a853700920
- Size of remote file:
- 30.3 MB
- SHA256:
- ddf2a231b037abd5392458a480d0ef1cf82e1633f20bb11aa507a677e2ba61e8
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