Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use mukish45/finetuned_bert_sentiment_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mukish45/finetuned_bert_sentiment_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mukish45/finetuned_bert_sentiment_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mukish45/finetuned_bert_sentiment_classification") model = AutoModelForSequenceClassification.from_pretrained("mukish45/finetuned_bert_sentiment_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mukish45/finetuned_bert_sentiment_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/mukish45/finetuned_bert_sentiment_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://mukish45/finetuned_bert_sentiment_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mukish45/finetuned_bert_sentiment_classification/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- a87feaebbf9920e18f921bad6dd48b50e77a906af2b15ad38a82096c452e31bc
- Size of remote file:
- 4.6 kB
- SHA256:
- 27ba1fc636aa69d7bee2e7f35ac8d491399737f6a20c309c06536ff7a32a301c
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