Instructions to use satishsingh90/deepak_deberta_v3_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use satishsingh90/deepak_deberta_v3_base with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="satishsingh90/deepak_deberta_v3_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("satishsingh90/deepak_deberta_v3_base") model = AutoModelForQuestionAnswering.from_pretrained("satishsingh90/deepak_deberta_v3_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from satishsingh90/deepak_deberta_v3_base: direct link, hf CLI and curl.
- Browser
- Download file 2.23 kB
-
https://huggingface.co/satishsingh90/deepak_deberta_v3_base/resolve/main/training_args.bin
- Command line
-
hf download hf://satishsingh90/deepak_deberta_v3_base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/satishsingh90/deepak_deberta_v3_base/resolve/main/training_args.bin
2.23 kB
- Xet hash:
- 05a35aa18653b3193b856464f3504d1f14614366b1e7a217d1392d1436f42ead
- Size of remote file:
- 2.23 kB
- SHA256:
- 70344f326e3b225b2e4500bab62aaad165f5a90b6a1672a4a8cc733b7eb2970c
路
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