Question Answering
Transformers
PyTorch
TensorFlow
Safetensors
PEFT
English
deberta-v2
deberta
deberta-v3
squad
squad_v2
lora
Eval Results (legacy)
Instructions to use sjrhuschlee/deberta-v3-large-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sjrhuschlee/deberta-v3-large-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="sjrhuschlee/deberta-v3-large-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sjrhuschlee/deberta-v3-large-squad2") model = AutoModelForQuestionAnswering.from_pretrained("sjrhuschlee/deberta-v3-large-squad2", device_map="auto") - PEFT
How to use sjrhuschlee/deberta-v3-large-squad2 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sjrhuschlee/deberta-v3-large-squad2: direct link, hf CLI and curl.
- Browser
- Download file 1.74 GB
-
https://huggingface.co/sjrhuschlee/deberta-v3-large-squad2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sjrhuschlee/deberta-v3-large-squad2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sjrhuschlee/deberta-v3-large-squad2/resolve/main/pytorch_model.bin
1.74 GB
- Xet hash:
- 01bd29658ad1b5785f5eb6515bd6ceff9a3b0de66c07d77645a6823ae25d0cfe
- Size of remote file:
- 1.74 GB
- SHA256:
- 96b28441f15018352c6a4786a32a5ae99a2c443d1f4f5527693c6b156844593e
路
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