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
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Download README.md from test992/colfixture: direct link, hf CLI and curl.
- Browser
- Download file 316 Bytes
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https://huggingface.co/test992/colfixture/resolve/main/README.md
- Command line
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hf download hf://test992/colfixture/README.md
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curl -L -o README.md https://huggingface.co/test992/colfixture/resolve/main/README.md
316 Bytes
metadata
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