Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use sasi2400/IntangibleBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sasi2400/IntangibleBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sasi2400/IntangibleBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sasi2400/IntangibleBERT") model = AutoModelForSequenceClassification.from_pretrained("sasi2400/IntangibleBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sasi2400/IntangibleBERT: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/sasi2400/IntangibleBERT/resolve/refs%2Fpr%2F13/training_args.bin
- Command line
-
hf download hf://sasi2400/IntangibleBERT@refs/pr/13/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sasi2400/IntangibleBERT/resolve/refs%2Fpr%2F13/training_args.bin
3.96 kB
- Xet hash:
- 4d054fae741bff75d2fc4acf495671ea1a8e71e3ee936de0a7c7f4ccd07488da
- Size of remote file:
- 3.96 kB
- SHA256:
- b3be03ca1d5403deeae616e02eae5f045acd73a8fd1926e71555bb8e8cfdd276
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