Text Classification
Transformers
TensorBoard
Safetensors
bert
HHD
10_class
multi_labels
Generated from Trainer
text-embeddings-inference
Instructions to use tjsgk/bert_model_out with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tjsgk/bert_model_out with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tjsgk/bert_model_out")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tjsgk/bert_model_out") model = AutoModelForSequenceClassification.from_pretrained("tjsgk/bert_model_out", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tjsgk/bert_model_out: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/tjsgk/bert_model_out/resolve/main/training_args.bin
- Command line
-
hf download hf://tjsgk/bert_model_out/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tjsgk/bert_model_out/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- c723c25953c73ab90c8d404a2f6bf250bb9361fcd935ea2a193c52ff5e6ec712
- Size of remote file:
- 5.37 kB
- SHA256:
- 0dc4bf9ae499122607937f73f5235c68c896e634b7ba2a47a5bfed2aa8bcba5a
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