Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use bamb1no/trainer_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bamb1no/trainer_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bamb1no/trainer_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bamb1no/trainer_output") model = AutoModelForSequenceClassification.from_pretrained("bamb1no/trainer_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee9bde1ede827179ae809d689c5c0808bf7ed455a2b75605502d9dd9bfc21c4d
- Size of remote file:
- 5.43 kB
- SHA256:
- 33765a9a444efde456ef025f212baab011986fc6263713faaf2043112fad7a1e
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