Translation
Transformers
PyTorch
Safetensors
English
t5
text2text-generation
retrieval
document-expansion
text-generation-inference
Instructions to use macavaney/doc2query-t5-base-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macavaney/doc2query-t5-base-msmarco with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" 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("translation", model="macavaney/doc2query-t5-base-msmarco")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("macavaney/doc2query-t5-base-msmarco") model = AutoModelForSeq2SeqLM.from_pretrained("macavaney/doc2query-t5-base-msmarco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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- text: "The presence of communication amid scientific minds was equally important to the success of the Manhattan Project as scientific intellect was. The only cloud hanging over the impressive achievement of the atomic researchers and engineers is what their success truly meant; hundreds of thousands of innocent lives obliterated."
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example_title: "msmarco-passage"
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widget:
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- text: "The presence of communication amid scientific minds was equally important to the success of the Manhattan Project as scientific intellect was. The only cloud hanging over the impressive achievement of the atomic researchers and engineers is what their success truly meant; hundreds of thousands of innocent lives obliterated."
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example_title: "msmarco-passage"
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