Text Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
reward-trainer
text-embeddings-inference
Instructions to use bdvs/trainer_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bdvs/trainer_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bdvs/trainer_output")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bdvs/trainer_output") model = AutoModelForSequenceClassification.from_pretrained("bdvs/trainer_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 740ac1e5a3cb260bdfa2bfe19386a7d2f841e0c5cba5115c425be9a6ca3e9d42
- Size of remote file:
- 538 MB
- SHA256:
- 724579de3b61999734f08cdca21b42e5d9d1f69a32a35e4db40ab962e2e6dba5
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