Text Classification
Transformers
Safetensors
English
bert
distillation
eamkd
tinybert
text-embeddings-inference
Instructions to use HFTrails/Distilled-Model-HX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HFTrails/Distilled-Model-HX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HFTrails/Distilled-Model-HX")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HFTrails/Distilled-Model-HX") model = AutoModelForSequenceClassification.from_pretrained("HFTrails/Distilled-Model-HX") - Notebooks
- Google Colab
- Kaggle
π’ Project Status
The model information and detailed documentation are currently under active update. Comprehensive model cards will be released progressively. Stay tuned!
This is a distilled model trained on the HX dataset. The one trained on the LH dataset can be found at Distilled-Model-LH.
- Downloads last month
- 7