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:
- 3f3d7430571b253913cf74453a262cb9ee65d9eeb698ee2c525d373a3f040552
- Size of remote file:
- 30.3 MB
- SHA256:
- 953e04fc639f4e7f5f38c0d2b5197167839f7637eee42dad6f1d5407ba14d3fa
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