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") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 365 Bytes
ab0bdf5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": true,
"mask_token": "[MASK]",
"name_or_path": "AutoTrain",
"never_split": null,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"special_tokens_map_file": null,
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"unk_token": "[UNK]"
}
|