Text Classification
Transformers
Safetensors
xlm-roberta
finance
financial-sentiment
sentiment-analysis
multilingual
financial-news
fintech
trading
market-sentiment
cross-lingual
text-embeddings-inference
Instructions to use Kenpache/finbert-multilingual-v2-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kenpache/finbert-multilingual-v2-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kenpache/finbert-multilingual-v2-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kenpache/finbert-multilingual-v2-large") model = AutoModelForSequenceClassification.from_pretrained("Kenpache/finbert-multilingual-v2-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "add_prefix_space": true, | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "XLMRobertaTokenizer", | |
| "unk_token": "<unk>" | |
| } |