Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Necraatall/Bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Necraatall/Bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Necraatall/Bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Necraatall/Bert") model = AutoModelForSequenceClassification.from_pretrained("Necraatall/Bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Necraatall/Bert: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/Necraatall/Bert/resolve/main/training_args.bin
- Command line
-
hf download hf://Necraatall/Bert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Necraatall/Bert/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- b4758449c2663992383599235c01be480b1cb8a895bffec2e5b7a1b8f3f30c45
- Size of remote file:
- 4.66 kB
- SHA256:
- 4e591eef11dfa9f606c95b47bc423529e8699253520853b8e8d39448e52baaf0
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