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:
- 309941a8b65a8d7bd5007edf0f24c956617ffa990a1d8ab0945251ab9ab22bcb
- Size of remote file:
- 4.09 kB
- SHA256:
- 8170c4b81cdb1294e03e959c557f6e274cb5dcb6d93eb7ecd43867d0f53c8170
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