Instructions to use snare2000/irl_mlm_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use snare2000/irl_mlm_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="snare2000/irl_mlm_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("snare2000/irl_mlm_model") model = AutoModelForMaskedLM.from_pretrained("snare2000/irl_mlm_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e79e448df4a3c94a3a5fbbe40c07e128c11d72e968bb13ee7073d93114d9c00a
- Size of remote file:
- 438 MB
- SHA256:
- 3040d90ebb7b59b4ba5643417586483635e5d49e94d222f0d888282bba744e2b
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