Text Classification
Transformers
Safetensors
English
ultrabert
finance
sentiment-analysis
financial-sentiment-analysis
custom_code
fp16
Eval Results (legacy)
Instructions to use beethogedeon/UltraFinBERT-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beethogedeon/UltraFinBERT-150M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="beethogedeon/UltraFinBERT-150M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("beethogedeon/UltraFinBERT-150M", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("beethogedeon/UltraFinBERT-150M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download data_audit.json from beethogedeon/UltraFinBERT-150M: direct link, hf CLI and curl.
- Browser
- Download file 647 Bytes
-
https://huggingface.co/beethogedeon/UltraFinBERT-150M/resolve/main/data_audit.json
- Command line
-
hf download hf://beethogedeon/UltraFinBERT-150M/data_audit.json
-
curl -L -o data_audit.json https://huggingface.co/beethogedeon/UltraFinBERT-150M/resolve/main/data_audit.json
647 Bytes
| { | |
| "raw_rows": 2264, | |
| "encoding": "cp1252", | |
| "conflict_groups": 0, | |
| "conflict_rows_removed": 0, | |
| "duplicate_rows_removed": 5, | |
| "retained_rows": 2259, | |
| "raw_label_counts": { | |
| "neutral": 1391, | |
| "positive": 570, | |
| "negative": 303 | |
| }, | |
| "retained_label_counts": { | |
| "neutral": 1386, | |
| "positive": 570, | |
| "negative": 303 | |
| }, | |
| "source_sha256": "5fb370b3005b9a2759f708849a691ad2e4d2593d4c995c1afde229398a516594", | |
| "source": "provided TXT file", | |
| "split_strategy_note": "Stratified 70/15/15 split generated from TXT with seed 42 (fallback mode)", | |
| "split_sizes": { | |
| "train": 1581, | |
| "validation": 339, | |
| "test": 339 | |
| } | |
| } |