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 pytorch_model.bin from ikim-uk-essen/GBERT-BioM-Translation-large: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/ikim-uk-essen/GBERT-BioM-Translation-large/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://ikim-uk-essen/GBERT-BioM-Translation-large@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ikim-uk-essen/GBERT-BioM-Translation-large/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.34 GB
- Xet hash:
- e8e112d4387010605a80bccb513f8eee43ca2b86d8d5624ffa4f1b541e0052ce
- Size of remote file:
- 1.34 GB
- SHA256:
- 2aa55ff8974284cb52021f247403a5d9b8f33bf274cfbb40517698ac86bc0ca5
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