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:
- 726e59d10f9a1bf23a326117381306b8564c3fff07947256326ce1d509b904bb
- Size of remote file:
- 30.3 MB
- SHA256:
- 2c6fc0b3b9756bc7921de0fe3cb371a4dd78e7d8731ecd30e1323d2ccfcfb826
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