Instructions to use Arvnd03/FirstTry with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arvnd03/FirstTry with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Arvnd03/FirstTry")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Arvnd03/FirstTry") model = AutoModelForSequenceClassification.from_pretrained("Arvnd03/FirstTry", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 030be0393ab292faca4260d013556941a80c84ca7b1e8a09284f9903a4e77231
- Size of remote file:
- 3.45 kB
- SHA256:
- d102fc34ba616ee13b2d0e2b4f7b00f1aa6e902d385148349f850f9313781dbb
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