Text Classification
Transformers
Safetensors
English
bert
federated-learning
finance
sentiment-analysis
finbert
fedavg
text-embeddings-inference
Instructions to use harshprasad03/FinBERT-FedAvg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harshprasad03/FinBERT-FedAvg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harshprasad03/FinBERT-FedAvg")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harshprasad03/FinBERT-FedAvg") model = AutoModelForSequenceClassification.from_pretrained("harshprasad03/FinBERT-FedAvg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from harshprasad03/FinBERT-FedAvg: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/harshprasad03/FinBERT-FedAvg/resolve/main/tokenizer.json
- Command line
-
hf download hf://harshprasad03/FinBERT-FedAvg/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/harshprasad03/FinBERT-FedAvg/resolve/main/tokenizer.json
712 kB
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