Text Classification
Transformers
TensorBoard
Safetensors
English
multilingual
xlm-roberta
financial-filings
Trained with AutoTrain
Eval Results (legacy)
text-embeddings-inference
Instructions to use FinancialReports/filing-classification-xlmr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinancialReports/filing-classification-xlmr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FinancialReports/filing-classification-xlmr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FinancialReports/filing-classification-xlmr") model = AutoModelForSequenceClassification.from_pretrained("FinancialReports/filing-classification-xlmr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4375ca9bfe891214ca57c98421f9bd331281cfd7f968d92883f543b8c81cf6c
- Size of remote file:
- 5.43 kB
- SHA256:
- e5a0ffcbb8ccb0f6e985e63284c804f39336b5affd2ee721120447b8d48d938b
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