Instructions to use srmishra/finetuning-sentiment-model-for-c2er with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srmishra/finetuning-sentiment-model-for-c2er with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="srmishra/finetuning-sentiment-model-for-c2er")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("srmishra/finetuning-sentiment-model-for-c2er") model = AutoModelForSequenceClassification.from_pretrained("srmishra/finetuning-sentiment-model-for-c2er") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9d0de51a6ee2180134e8fd02d27a7a8dae74a0527b0890a666635ad56eeea66
- Size of remote file:
- 268 MB
- SHA256:
- 5c335aca6cf55e84ba5391e5b694d2630f47c80d8e770c10d0bf1b33f189e894
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