Instructions to use ashdev01/my_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashdev01/my_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ashdev01/my_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ashdev01/my_model") model = AutoModelForMaskedLM.from_pretrained("ashdev01/my_model") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files
README.md
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license: apache-2.0
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base_model: distilbert/distilroberta-base
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tags:
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- generated_from_trainer
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model-index:
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---
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base_model: distilbert/distilroberta-base
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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