Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use javierorjuela/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use javierorjuela/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="javierorjuela/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("javierorjuela/results") model = AutoModelForSequenceClassification.from_pretrained("javierorjuela/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0f0480ce3b989f36d509db510a29c64b45bd9baafdcdeda008a35040cfb15d6
- Size of remote file:
- 5.11 kB
- SHA256:
- 57432a9adc605f3aa36f9b39bf762b1d6094466689e2d90c6cbd6ee01633b62f
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