Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use nonsodev/datrix-text-classification-job_1150db04 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nonsodev/datrix-text-classification-job_1150db04 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nonsodev/datrix-text-classification-job_1150db04")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nonsodev/datrix-text-classification-job_1150db04") model = AutoModelForSequenceClassification.from_pretrained("nonsodev/datrix-text-classification-job_1150db04", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1467e90c0f277bd014e35024bd26b3ad68863843d50dd46556d559164e6a38d6
- Size of remote file:
- 5.33 kB
- SHA256:
- f64d0c30a337e7f518c95fae4979844ae96125fc7a82b9f0457463987daf558c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.