Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use quant-chef/trial-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quant-chef/trial-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="quant-chef/trial-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("quant-chef/trial-model") model = AutoModelForSequenceClassification.from_pretrained("quant-chef/trial-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from quant-chef/trial-model: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/quant-chef/trial-model/resolve/main/training_args.bin
- Command line
-
hf download hf://quant-chef/trial-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/quant-chef/trial-model/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- e79696fac57e1369b3ba1de5f1bb9700de9ec39a6408b96190fdcf6953168c73
- Size of remote file:
- 4.6 kB
- SHA256:
- 477850085a2bd7daca54670d83d4311a9a68bb9273bfc0c3fced9042b25ba882
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