Instructions to use Neil96/mymodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Neil96/mymodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Neil96/mymodel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Neil96/mymodel") model = AutoModelForSequenceClassification.from_pretrained("Neil96/mymodel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 043633dff5949414ad2a8a1692492f3f0cf328bdb8d19f048e6e3de37c142757
- Size of remote file:
- 331 MB
- SHA256:
- 100460c20b6deba98aae8fb8376d9509cc39f851197198979b37ac538a24499c
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