Question Answering
Transformers
PyTorch
Safetensors
English
roberta
chemistry
contamination
waterborne
question answering
Instructions to use Galahad3x/QAModelForPatho with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Galahad3x/QAModelForPatho 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="Galahad3x/QAModelForPatho")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Galahad3x/QAModelForPatho") model = AutoModelForQuestionAnswering.from_pretrained("Galahad3x/QAModelForPatho", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Galahad3x/QAModelForPatho: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Galahad3x/QAModelForPatho/resolve/main/training_args.bin
- Command line
-
hf download hf://Galahad3x/QAModelForPatho/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Galahad3x/QAModelForPatho/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- d5319ab5d0e4083f3a2e3e67ac26f89e4ec9e64ccd1e5555a60f7a2821476eb2
- Size of remote file:
- 3.52 kB
- SHA256:
- 2c0b8c15dbeeed4a664b6af349671c4970fd308deb32038b812f3dfff79e391f
路
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