Instructions to use peft-internal-testing/tiny-random-RobertaForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peft-internal-testing/tiny-random-RobertaForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="peft-internal-testing/tiny-random-RobertaForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("peft-internal-testing/tiny-random-RobertaForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("peft-internal-testing/tiny-random-RobertaForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from peft-internal-testing/tiny-random-RobertaForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 349 kB
-
https://huggingface.co/peft-internal-testing/tiny-random-RobertaForSequenceClassification/resolve/main/model.safetensors
- Command line
-
hf download hf://peft-internal-testing/tiny-random-RobertaForSequenceClassification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/peft-internal-testing/tiny-random-RobertaForSequenceClassification/resolve/main/model.safetensors
349 kB
- Xet hash:
- b135019c35a8d18f994146cf6bbef27ff02b4daff76258f3a71a2a8d565eebd1
- Size of remote file:
- 349 kB
- SHA256:
- e3750b3b71c8b41a5d1c5c0745f37d14539e2fcfb73319bb37b9a2db5990ee5b
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