Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use artarif/trainer_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use artarif/trainer_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="artarif/trainer_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("artarif/trainer_output") model = AutoModelForSequenceClassification.from_pretrained("artarif/trainer_output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 628ed22885ea6a5c125d126c53be9a5a6570f81adb73c51997ec6183fd721cc9
- Size of remote file:
- 5.37 kB
- SHA256:
- 08ab124f486b4e119a41d214d5dae2296647e5dffeb189f2fb2ad7e2cbc000d5
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