Instructions to use hf-tiny-model-private/tiny-random-BartForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-BartForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-BartForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BartForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-BartForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-BartForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 120 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-BartForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-BartForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-BartForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
120 kB
- Xet hash:
- 90ec02df22514b333370c50c1aea067f066a756787738417603d6fc5a8ad3351
- Size of remote file:
- 120 kB
- SHA256:
- 473b9b2eece3f56b543d464feb78c9dd94b1af9b61ecfbc2d32b94851633c9eb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.