Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use aloeme/trainer_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aloeme/trainer_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aloeme/trainer_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aloeme/trainer_output") model = AutoModelForSequenceClassification.from_pretrained("aloeme/trainer_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57b1dec7fc50f162034a01f732f9adad92637a09eb70a00df5266f8ae92993a3
- Size of remote file:
- 538 MB
- SHA256:
- 8967577f7128cbc41c2983ce5354b3eb2df606eae106bd54be1addf022bd9e87
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