Instructions to use roselyu/FinSent-XLMR-FinNews with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roselyu/FinSent-XLMR-FinNews with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="roselyu/FinSent-XLMR-FinNews")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("roselyu/FinSent-XLMR-FinNews") model = AutoModelForSequenceClassification.from_pretrained("roselyu/FinSent-XLMR-FinNews", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from roselyu/FinSent-XLMR-FinNews: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/roselyu/FinSent-XLMR-FinNews/resolve/main/tokenizer.json
- Command line
-
hf download hf://roselyu/FinSent-XLMR-FinNews/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/roselyu/FinSent-XLMR-FinNews/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- a6f245d5141ef77b3b89d7b7b9abc5ffcc095aad2908a46268b077c87d7319b6
- Size of remote file:
- 17.1 MB
- SHA256:
- 69564b696052886ed0ac63fa393e928384e0f8caada38c1f4864a9bfbf379c15
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