Instructions to use abazoge/DrBERT-4096 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abazoge/DrBERT-4096 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="abazoge/DrBERT-4096")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("abazoge/DrBERT-4096") model = AutoModelForMaskedLM.from_pretrained("abazoge/DrBERT-4096", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from abazoge/DrBERT-4096: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/abazoge/DrBERT-4096/resolve/main/training_args.bin
- Command line
-
hf download hf://abazoge/DrBERT-4096/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/abazoge/DrBERT-4096/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- f0fb795a08b71c8e1043d87fbfb6b0a485d17b0a76fcb99c64eec5ddd4b3d6fc
- Size of remote file:
- 3.44 kB
- SHA256:
- 6f79061a090b4c98c3846833bf02347560e8fe3b2ced5fde608ffe518f6330fe
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