Instructions to use test992/colfixture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use test992/colfixture with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="test992/colfixture")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("test992/colfixture", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 316 Bytes
731bc0a 97ce207 731bc0a 97ce207 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ---
library_name: transformers
pipeline_tag: text-classification
widget:
- text: "I love this movie"
example_title: "Example 1"
output:
- label: "<img src=x onerror=window.WX1=1>"
score: 0.91
- text: "I hate this movie"
example_title: "Example 2"
output:
- label: "NEGATIVE"
score: 0.88
---
# wx
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