Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
DEV
Eval Results (legacy)
text-embeddings-inference
Instructions to use FinanceInc/auditor_sentiment_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinanceInc/auditor_sentiment_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FinanceInc/auditor_sentiment_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FinanceInc/auditor_sentiment_finetuned") model = AutoModelForSequenceClassification.from_pretrained("FinanceInc/auditor_sentiment_finetuned", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from FinanceInc/auditor_sentiment_finetuned: direct link, hf CLI and curl.
- Browser
- Download file 439 MB
-
https://huggingface.co/FinanceInc/auditor_sentiment_finetuned/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://FinanceInc/auditor_sentiment_finetuned/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FinanceInc/auditor_sentiment_finetuned/resolve/main/pytorch_model.bin
439 MB
- Xet hash:
- ec822c02c3dec02f4015f041044170a23963a8aea6670b6e76a6c8475b0ccdc4
- Size of remote file:
- 439 MB
- SHA256:
- 2092476524bf609bfc3a5703076501e729f27435f51991e2105f272be7195853
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