Text Classification
Transformers
ONNX
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use tmtryggingar/payment-codes-classifier-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tmtryggingar/payment-codes-classifier-dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tmtryggingar/payment-codes-classifier-dev")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tmtryggingar/payment-codes-classifier-dev") model = AutoModelForSequenceClassification.from_pretrained("tmtryggingar/payment-codes-classifier-dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tmtryggingar/payment-codes-classifier-dev: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/tmtryggingar/payment-codes-classifier-dev/resolve/main/training_args.bin
- Command line
-
hf download hf://tmtryggingar/payment-codes-classifier-dev/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tmtryggingar/payment-codes-classifier-dev/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- df43b31c9bbb47724400d61b80601717dc8d855f8632fecf08b0e5c4106487aa
- Size of remote file:
- 5.84 kB
- SHA256:
- 44a2cab0381b7208445b81419a484b4591c759e748e7a396db7c7a2a40fcdab6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.