Instructions to use chiranthans23/my-test-mlm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chiranthans23/my-test-mlm-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="chiranthans23/my-test-mlm-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("chiranthans23/my-test-mlm-model") model = AutoModelForMaskedLM.from_pretrained("chiranthans23/my-test-mlm-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3b8817dc1caf3353a7880d9f7e598a07b00921a9ff28b91a3f05eca0c984d69
- Size of remote file:
- 438 MB
- SHA256:
- c46abe254b96adca3866dcfcd808bbd8d4dbbe6b13da81aedf7d7a1407f429d8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.