Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use sprx7767/trial-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sprx7767/trial-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sprx7767/trial-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sprx7767/trial-model") model = AutoModelForSequenceClassification.from_pretrained("sprx7767/trial-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sprx7767/trial-model: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/sprx7767/trial-model/resolve/main/training_args.bin
- Command line
-
hf download hf://sprx7767/trial-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sprx7767/trial-model/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 821bb4149829d9a1a3846274566eea438339fe548ff4cbd1411da839688b8214
- Size of remote file:
- 4.6 kB
- SHA256:
- 1ef3f0427ce45cda305b0cd9836576c2e8cfc41a0f6366c355b9227f40d82094
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