Instructions to use donal/Pro_Berta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use donal/Pro_Berta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="donal/Pro_Berta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("donal/Pro_Berta") model = AutoModelForMaskedLM.from_pretrained("donal/Pro_Berta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from donal/Pro_Berta: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/donal/Pro_Berta/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://donal/Pro_Berta@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/donal/Pro_Berta/resolve/refs%2Fpr%2F1/pytorch_model.bin
336 MB
- Xet hash:
- 5bbe79e7b07087657bc23a63df5f748052d912c60b6e26a739a0f5c24feee637
- Size of remote file:
- 336 MB
- SHA256:
- 4fb0de6512996f3612e0e4a49b6c12b7e88eace4c6279c8ed917de12acb32c6c
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