Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use asimokby/bert_gec_detect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asimokby/bert_gec_detect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="asimokby/bert_gec_detect")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("asimokby/bert_gec_detect") model = AutoModelForSequenceClassification.from_pretrained("asimokby/bert_gec_detect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from asimokby/bert_gec_detect: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/asimokby/bert_gec_detect/resolve/main/training_args.bin
- Command line
-
hf download hf://asimokby/bert_gec_detect/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/asimokby/bert_gec_detect/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- fb160e7ac352575b99a6e34b20bd7a5f0a888b36baba89063618ef95b01afded
- Size of remote file:
- 4.66 kB
- SHA256:
- 0b55d852a24ba1a9024517b1deb857fed1b8e9a18771e631976455848fb4c2a1
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