Instructions to use peft-internal-testing/tiny-random-DebertaModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peft-internal-testing/tiny-random-DebertaModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="peft-internal-testing/tiny-random-DebertaModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("peft-internal-testing/tiny-random-DebertaModel") model = AutoModel.from_pretrained("peft-internal-testing/tiny-random-DebertaModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from peft-internal-testing/tiny-random-DebertaModel: direct link, hf CLI and curl.
- Browser
- Download file 341 kB
-
https://huggingface.co/peft-internal-testing/tiny-random-DebertaModel/resolve/main/model.safetensors
- Command line
-
hf download hf://peft-internal-testing/tiny-random-DebertaModel/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/peft-internal-testing/tiny-random-DebertaModel/resolve/main/model.safetensors
341 kB
- Xet hash:
- 327d09e00da39f0e2c3940cd6eb667b8c835711e6603a6d60f9b84b483476f9b
- Size of remote file:
- 341 kB
- SHA256:
- eab5ef63515cbc8d3a0daeb60a7ad1fe000bba0fc164d30788b0981b667065b5
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