Instructions to use NLPForUA/mdeberta-v3-ua-squad-reader with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLPForUA/mdeberta-v3-ua-squad-reader 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="NLPForUA/mdeberta-v3-ua-squad-reader")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("NLPForUA/mdeberta-v3-ua-squad-reader") model = AutoModelForQuestionAnswering.from_pretrained("NLPForUA/mdeberta-v3-ua-squad-reader", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from NLPForUA/mdeberta-v3-ua-squad-reader: direct link, hf CLI and curl.
- Browser
- Download file 16 MB
-
https://huggingface.co/NLPForUA/mdeberta-v3-ua-squad-reader/resolve/main/tokenizer.json
- Command line
-
hf download hf://NLPForUA/mdeberta-v3-ua-squad-reader/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/NLPForUA/mdeberta-v3-ua-squad-reader/resolve/main/tokenizer.json
16 MB
- Xet hash:
- 0751250d2a52a9953b8b629b0845656d4c35b40726afb4f19d0a318fbe05303a
- Size of remote file:
- 16 MB
- SHA256:
- b6feb9250af3396939401534b05c35280394140fcc7256c1357e21e852e062d8
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