Text Classification
Transformers
PyTorch
English
bert
pubmed
arxiv
representations
scientific documents
text-embeddings-inference
Instructions to use arazd/MIReAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arazd/MIReAD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="arazd/MIReAD")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("arazd/MIReAD") model = AutoModelForSequenceClassification.from_pretrained("arazd/MIReAD") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 251f8fc50d604e7db5f6ffe31f437263a9b8257d6c94e4c3d2b46b34902c7628
- Size of remote file:
- 448 MB
- SHA256:
- 6ac33c26305614ef1228a4f3817f1972e9f48df405361e4a6a69a1aef8a958fe
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