Text Classification
Transformers
PyTorch
Portuguese
xlm-roberta
msmarco
miniLM
tensorflow
pt-br
text-embeddings-inference
Instructions to use unicamp-dl/mMiniLM-L6-v2-mmarco-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unicamp-dl/mMiniLM-L6-v2-mmarco-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="unicamp-dl/mMiniLM-L6-v2-mmarco-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("unicamp-dl/mMiniLM-L6-v2-mmarco-v2") model = AutoModelForSequenceClassification.from_pretrained("unicamp-dl/mMiniLM-L6-v2-mmarco-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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