Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use dpazmino/finetuning-sentiment-model_duke_final_two with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dpazmino/finetuning-sentiment-model_duke_final_two with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dpazmino/finetuning-sentiment-model_duke_final_two")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dpazmino/finetuning-sentiment-model_duke_final_two") model = AutoModelForSequenceClassification.from_pretrained("dpazmino/finetuning-sentiment-model_duke_final_two", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28b065ba07734cc19140855951849d79d7ea00b50e8487ff1e7af944c0cdc6c9
- Size of remote file:
- 3.12 kB
- SHA256:
- 4a6f793a1b6f826341ff0c72f2764ac11f3f65d4dc2e4ffe7c26aa91407a2c30
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