Instructions to use hitachi-nlp/roberta-base_first-char_acl2023 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hitachi-nlp/roberta-base_first-char_acl2023 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hitachi-nlp/roberta-base_first-char_acl2023")# Load model directly from transformers import AutoTokenizer, RobertaForFirstCharPrediction tokenizer = AutoTokenizer.from_pretrained("hitachi-nlp/roberta-base_first-char_acl2023") model = RobertaForFirstCharPrediction.from_pretrained("hitachi-nlp/roberta-base_first-char_acl2023", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hitachi-nlp/roberta-base_first-char_acl2023: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/hitachi-nlp/roberta-base_first-char_acl2023/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hitachi-nlp/roberta-base_first-char_acl2023/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hitachi-nlp/roberta-base_first-char_acl2023/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 61b8a166de540fdd67fc7093e067f8c32d87387d8ff8b0ef0e5287379545abda
- Size of remote file:
- 499 MB
- SHA256:
- 29dd2027aea1daf8cbb37b58e2e868b8b5e9df6b1a7350d9421d810c26fbc704
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