Instructions to use deepset/tinybert-6l-768d-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/tinybert-6l-768d-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="deepset/tinybert-6l-768d-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/tinybert-6l-768d-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/tinybert-6l-768d-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/tinybert-6l-768d-squad2: direct link, hf CLI and curl.
- Browser
- Download file 266 MB
-
https://huggingface.co/deepset/tinybert-6l-768d-squad2/resolve/e072efb2fe1a00fe3972b3bc43ae59ffe7812585/pytorch_model.bin
- Command line
-
hf download hf://deepset/tinybert-6l-768d-squad2@e072efb2fe1a00fe3972b3bc43ae59ffe7812585/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/tinybert-6l-768d-squad2/resolve/e072efb2fe1a00fe3972b3bc43ae59ffe7812585/pytorch_model.bin
266 MB
- Xet hash:
- e357bc47a4a0ee04a1a9091987dd29685b7aec6c9a0199753dd00c94908f8e2d
- Size of remote file:
- 266 MB
- SHA256:
- a760914cbb77e886edc814b1101cffb8a65d4b7722ee7b1338279091d5d33a77
路
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