Instructions to use hf-tiny-model-private/tiny-random-RoCBertForSequenceClassification 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-RoCBertForSequenceClassification 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-RoCBertForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RoCBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-RoCBertForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-RoCBertForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 2.97 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-RoCBertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-RoCBertForSequenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-RoCBertForSequenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
2.97 MB
- Xet hash:
- 10dd24d4665534a567eeb45f344e17df36d371571740d558a5f2d5b1c7a529d8
- Size of remote file:
- 2.97 MB
- SHA256:
- cfec7138ec8321758eb079eda722724d60e5285f19ed374a444655f48fc4a1a5
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