Instructions to use dany0407/MLM_rotten_tomatoes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dany0407/MLM_rotten_tomatoes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dany0407/MLM_rotten_tomatoes")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dany0407/MLM_rotten_tomatoes") model = AutoModelForMaskedLM.from_pretrained("dany0407/MLM_rotten_tomatoes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5315f6298d12e0bd789e88c41def80d340165304e09eb237f6b5614f892ea00
- Size of remote file:
- 5.71 kB
- SHA256:
- 2a428d8f251aca9c0f67a7622f0ba856296a5ef07d4acd3f09dd1bf3189beb5d
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