Text Classification
Transformers
ONNX
Safetensors
English
distilbert
trading
intent-classification
lora
english
text-embeddings-inference
Instructions to use DoDataThings/distilbert-trade-decision-classifier-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DoDataThings/distilbert-trade-decision-classifier-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DoDataThings/distilbert-trade-decision-classifier-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DoDataThings/distilbert-trade-decision-classifier-v1") model = AutoModelForSequenceClassification.from_pretrained("DoDataThings/distilbert-trade-decision-classifier-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a5a16bc04a5d6bf43835249dcdf368040b4198a7d07025278eaf49d05103dc3
- Size of remote file:
- 59.1 kB
- SHA256:
- 7dfcb59f278c90ba702a929e57158720637042abe4637ab0afe17003961f5f5b
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