Instructions to use hf-tiny-model-private/tiny-random-IBertForSequenceClassification 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-IBertForSequenceClassification 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-IBertForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-IBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-IBertForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-IBertForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 729 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-IBertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-IBertForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-IBertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
729 kB
- Xet hash:
- 67ff9a43de03b4f5a4aad38cf31d071149a776d3d7ccdb8665df1f0ab53e5d79
- Size of remote file:
- 729 kB
- SHA256:
- 8226d7a84cd36fbac803a75d34bcc87bb35353e293e427abc6793d5b580ebd55
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.