Text Classification
Transformers
Safetensors
English
Thai
xlm-roberta
sentiment-analysis
financial-sentiment
multilingual
transformer
fine-tuned
1.0.0
text-embeddings-inference
Instructions to use ZombitX64/Fin-E5-pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZombitX64/Fin-E5-pro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZombitX64/Fin-E5-pro")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ZombitX64/Fin-E5-pro") model = AutoModelForSequenceClassification.from_pretrained("ZombitX64/Fin-E5-pro", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ZombitX64/Fin-E5-pro: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/ZombitX64/Fin-E5-pro/resolve/main/tokenizer.json
- Command line
-
hf download hf://ZombitX64/Fin-E5-pro/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ZombitX64/Fin-E5-pro/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 5b1eebf28d51b425919503bde32f76a54f1055eb4b3e3f6a03946174a9a2060d
- Size of remote file:
- 17.1 MB
- SHA256:
- cad551d5600a84242d0973327029452a1e3672ba6313c2a3c3d69c4310e12719
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