Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use BruceT02/DistilBert_Exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BruceT02/DistilBert_Exp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BruceT02/DistilBert_Exp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BruceT02/DistilBert_Exp") model = AutoModelForSequenceClassification.from_pretrained("BruceT02/DistilBert_Exp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| base_model: distilbert-base-uncased | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| model-index: | |
| - name: finetuning-sentiment-model-3000-samples | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| ### Framework versions | |
| - Transformers 4.41.2 | |
| - Pytorch 2.3.0+cu121 | |
| - Datasets 2.19.2 | |
| - Tokenizers 0.19.1 | |