Instructions to use nbroad/deb-base-gc2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/deb-base-gc2 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="nbroad/deb-base-gc2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nbroad/deb-base-gc2") model = AutoModelForQuestionAnswering.from_pretrained("nbroad/deb-base-gc2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nbroad/deb-base-gc2: direct link, hf CLI and curl.
- Browser
- Download file 277 MB
-
https://huggingface.co/nbroad/deb-base-gc2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nbroad/deb-base-gc2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nbroad/deb-base-gc2/resolve/main/pytorch_model.bin
277 MB
- Xet hash:
- 9b30adc943c76702ea0d88a380fd269fedcda1db2ddfa6b2e34befcfe296356d
- Size of remote file:
- 277 MB
- SHA256:
- 800420357a6f2163ec21310fcf77ad9b801f6aeb404cf8595bf4f3ff327ddf96
路
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