Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use vgarg/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vgarg/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vgarg/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vgarg/results") model = AutoModelForSequenceClassification.from_pretrained("vgarg/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from vgarg/results: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/vgarg/results/resolve/main/training_args.bin
- Command line
-
hf download hf://vgarg/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/vgarg/results/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 24763e92bc067e40dcd0d160804face23bbb82fe73e28901a2cf06bc5b86cb3c
- Size of remote file:
- 5.11 kB
- SHA256:
- b4927a335787cd07e598e2f4f5059a3198a6c30ef3d5d28c70350b967751b133
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