Instructions to use mohammadtari/arxivinterface with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammadtari/arxivinterface with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mohammadtari/arxivinterface") model = AutoModelForSeq2SeqLM.from_pretrained("mohammadtari/arxivinterface") - Notebooks
- Google Colab
- Kaggle
Quick Links
t5_small_summarization_model
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.15.0
- TensorFlow 2.7.0
- Datasets 1.17.0
- Tokenizers 0.10.3
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mohammadtari/arxivinterface") model = AutoModelForSeq2SeqLM.from_pretrained("mohammadtari/arxivinterface")