Instructions to use quangtqv/cross_encoder_tool_learning_24_7_2024_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quangtqv/cross_encoder_tool_learning_24_7_2024_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="quangtqv/cross_encoder_tool_learning_24_7_2024_test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("quangtqv/cross_encoder_tool_learning_24_7_2024_test") model = AutoModelForSequenceClassification.from_pretrained("quangtqv/cross_encoder_tool_learning_24_7_2024_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
9fcc948 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:6ba9aaf9ea4012b3012b5b285a0b28b1c5b5f1a9111b80d9ac2a5deba3b1a939
size 17098503
|