Instructions to use hosung1/roberta_small_mlm_from_scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hosung1/roberta_small_mlm_from_scratch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hosung1/roberta_small_mlm_from_scratch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hosung1/roberta_small_mlm_from_scratch") model = AutoModelForMaskedLM.from_pretrained("hosung1/roberta_small_mlm_from_scratch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hosung1/roberta_small_mlm_from_scratch: direct link, hf CLI and curl.
- Browser
- Download file 2.03 MB
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https://huggingface.co/hosung1/roberta_small_mlm_from_scratch/resolve/main/tokenizer.json
- Command line
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hf download hf://hosung1/roberta_small_mlm_from_scratch/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/hosung1/roberta_small_mlm_from_scratch/resolve/main/tokenizer.json
2.03 MB
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