Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Jios/bert-unformatted-network-data-test-ids-2018 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jios/bert-unformatted-network-data-test-ids-2018 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jios/bert-unformatted-network-data-test-ids-2018")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jios/bert-unformatted-network-data-test-ids-2018") model = AutoModelForSequenceClassification.from_pretrained("Jios/bert-unformatted-network-data-test-ids-2018", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Jios/bert-unformatted-network-data-test-ids-2018: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/Jios/bert-unformatted-network-data-test-ids-2018/resolve/main/tokenizer.json
- Command line
-
hf download hf://Jios/bert-unformatted-network-data-test-ids-2018/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Jios/bert-unformatted-network-data-test-ids-2018/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.