Instructions to use Jeska/BertjeWDialDataALLQonly07 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeska/BertjeWDialDataALLQonly07 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Jeska/BertjeWDialDataALLQonly07")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jeska/BertjeWDialDataALLQonly07") model = AutoModelForMaskedLM.from_pretrained("Jeska/BertjeWDialDataALLQonly07", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Jeska/BertjeWDialDataALLQonly07: direct link, hf CLI and curl.
- Browser
- Download file 437 MB
-
https://huggingface.co/Jeska/BertjeWDialDataALLQonly07/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jeska/BertjeWDialDataALLQonly07/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jeska/BertjeWDialDataALLQonly07/resolve/main/pytorch_model.bin
437 MB
- Xet hash:
- 1a93f028688c0f81403a2ba54f498ce13a4e9398807a895dee269549722c2069
- Size of remote file:
- 437 MB
- SHA256:
- 60c4feb771a71adbc42d1560faa43ed880c1f977515a3a4fe540ecc44ae9b6a6
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