Text Classification
Transformers
Safetensors
llama
Generated from Trainer
reward-trainer
trl
text-embeddings-inference
Instructions to use veraslip/trainer_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use veraslip/trainer_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="veraslip/trainer_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("veraslip/trainer_output") model = AutoModelForSequenceClassification.from_pretrained("veraslip/trainer_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from veraslip/trainer_output: direct link, hf CLI and curl.
- Browser
- Download file 6.03 kB
-
https://huggingface.co/veraslip/trainer_output/resolve/main/training_args.bin
- Command line
-
hf download hf://veraslip/trainer_output/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/veraslip/trainer_output/resolve/main/training_args.bin
6.03 kB
- Xet hash:
- aef449c65559280b7eb0281a635a808e1cea50bc079a4f3b2b40dcd7d5c10d6a
- Size of remote file:
- 6.03 kB
- SHA256:
- 6757e6b2d166f95bfeaa27547fe153aa1ad259021e3ac89b4d1a33fce5eefbde
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