Instructions to use deepakvk/albert-base-v2-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepakvk/albert-base-v2-squad2 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="deepakvk/albert-base-v2-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepakvk/albert-base-v2-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepakvk/albert-base-v2-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepakvk/albert-base-v2-squad2: direct link, hf CLI and curl.
- Browser
- Download file 44.4 MB
-
https://huggingface.co/deepakvk/albert-base-v2-squad2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepakvk/albert-base-v2-squad2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepakvk/albert-base-v2-squad2/resolve/main/pytorch_model.bin
44.4 MB
- Xet hash:
- c33f19deeb17b976dab2a47409e93c5c230c74a7337fa9edc1a9c94c06aa39c2
- Size of remote file:
- 44.4 MB
- SHA256:
- 51bdec027c0e942704afac07f195c9ce712b66182de7a447156af5592f5f4abc
路
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