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 model.safetensors from tmtryggingar/payment-codes-classifier-dev: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/tmtryggingar/payment-codes-classifier-dev/resolve/main/model.safetensors
- Command line
-
hf download hf://tmtryggingar/payment-codes-classifier-dev/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/tmtryggingar/payment-codes-classifier-dev/resolve/main/model.safetensors
1.42 GB
- Xet hash:
- 5b57cf68e0ccae5a3838ed5df37e05c59e323c4a03ef6fc83d76331300e794c6
- Size of remote file:
- 1.42 GB
- SHA256:
- bdee2a2424057e7072109ba3b08736990775a89a9ef1a49ebabc5b0d195014f6
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