Instructions to use ikim-uk-essen/GBERT-BioM-Translation-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ikim-uk-essen/GBERT-BioM-Translation-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ikim-uk-essen/GBERT-BioM-Translation-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ikim-uk-essen/GBERT-BioM-Translation-large") model = AutoModelForMaskedLM.from_pretrained("ikim-uk-essen/GBERT-BioM-Translation-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ikim-uk-essen/GBERT-BioM-Translation-large: direct link, hf CLI and curl.
- Browser
- Download file 4.14 kB
-
https://huggingface.co/ikim-uk-essen/GBERT-BioM-Translation-large/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://ikim-uk-essen/GBERT-BioM-Translation-large@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ikim-uk-essen/GBERT-BioM-Translation-large/resolve/refs%2Fpr%2F1/training_args.bin
4.14 kB
- Xet hash:
- 25527ddc9a6f163aa59031ffd3cc64574d52c079c0324a3daa7a068a70db1f8a
- Size of remote file:
- 4.14 kB
- SHA256:
- e548ff49c5d486f6416ed76fd7392dc6bc8f42f5c83a213070ba2a1a64ee4891
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