Instructions to use hf-internal-testing/tiny-random-PhiForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PhiForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-PhiForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PhiForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-PhiForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-PhiForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 189 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-PhiForSequenceClassification/resolve/refs%2Fpr%2F6/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-PhiForSequenceClassification@refs/pr/6/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-PhiForSequenceClassification/resolve/refs%2Fpr%2F6/model.safetensors
189 kB
- Xet hash:
- 484c0c24a3eae1f36a32d89b1ddc80ac49432f636ea2bf12ebb7c1db21957886
- Size of remote file:
- 189 kB
- SHA256:
- 5399aa765ea39806f46a81ba1bd80ebbf3088a26cf6d4e992c1f94a829d396ab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.