Instructions to use Akari/albert-base-v2-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akari/albert-base-v2-finetuned-squad 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="Akari/albert-base-v2-finetuned-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Akari/albert-base-v2-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("Akari/albert-base-v2-finetuned-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Akari/albert-base-v2-finetuned-squad: direct link, hf CLI and curl.
- Browser
- Download file 53.9 MB
-
https://huggingface.co/Akari/albert-base-v2-finetuned-squad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Akari/albert-base-v2-finetuned-squad/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Akari/albert-base-v2-finetuned-squad/resolve/main/pytorch_model.bin
53.9 MB
- Xet hash:
- 2b8dbbe3e9fca9c0f2d1917c5d5183967badf95970170114f0428aaf4854fffa
- Size of remote file:
- 53.9 MB
- SHA256:
- 105fb873788976a1a8fcfc852608770f438867a36dd21afc9fdefd89506f3cfc
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.