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
- Xet hash:
- 040ff09a2eb1f6061b5e2e872e6450502094a04a869ca76278d5ba7c353227fc
- Size of remote file:
- 5.18 kB
- SHA256:
- 34b4e71cc1ea5532c7eb89457197bedb71d46f63317130f23b7a3cda1f431db2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.