Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
4-bit precision
bitsandbytes
Instructions to use shirwu/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shirwu/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shirwu/output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shirwu/output") model = AutoModelForSequenceClassification.from_pretrained("shirwu/output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df93dd46bd3b0a1607f478da2f60969cdf82a43f702141716d3606ff0ec168dd
- Size of remote file:
- 671 MB
- SHA256:
- 0778175a61a5e04b66249489d7f7f7cf186338fc9edc60385396ca1618ad3e73
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