Instructions to use gm-akisame/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gm-akisame/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gm-akisame/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gm-akisame/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("gm-akisame/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f7f0cbd1ea328cc7f11a4958a87630204022d5d4cd6ecbf987b4acc40651bc0
- Size of remote file:
- 268 MB
- SHA256:
- 562979f539198cb8a59fcbd2f5ff2174a7f4e054242176a40db864794b9d6fbb
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