Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use janedsa/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use janedsa/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="janedsa/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("janedsa/model") model = AutoModelForSequenceClassification.from_pretrained("janedsa/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from janedsa/model: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/janedsa/model/resolve/main/training_args.bin
- Command line
-
hf download hf://janedsa/model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/janedsa/model/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- cd54397d44ff9b1e598f293a64d1dbe5d0495af0d16dcc27b8da60a98c88a324
- Size of remote file:
- 4.98 kB
- SHA256:
- 7b422c2e1b19308d7818ef9887cd11b3e69e1422e01d2bbc9a2462f62e900388
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