Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use nonsodev/datrix-text-classification-job_b0ca95b3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nonsodev/datrix-text-classification-job_b0ca95b3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nonsodev/datrix-text-classification-job_b0ca95b3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nonsodev/datrix-text-classification-job_b0ca95b3") model = AutoModelForSequenceClassification.from_pretrained("nonsodev/datrix-text-classification-job_b0ca95b3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf93eee054d2833841687b168c7901a851448e40ae04fb62cb6b79c995323e65
- Size of remote file:
- 5.33 kB
- SHA256:
- b0c3e6520affbd8a19e7dd010d4934a6817e9e82e4a44f8c3186feb23988ffda
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.