Instructions to use hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 321 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification/resolve/603343713a3240f40c25b990506ed1d438fb6592/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification@603343713a3240f40c25b990506ed1d438fb6592/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-GPTBigCodeForSequenceClassification/resolve/603343713a3240f40c25b990506ed1d438fb6592/pytorch_model.bin
321 kB
- Xet hash:
- 2890b669a54294beb51a1250ef9c12a46f2f69b8ecd955dd4815cf2007cb5b12
- Size of remote file:
- 321 kB
- SHA256:
- 44d79497b75ef0d1d7db55abf8c0834035ec521d2e954ed75cf61eaf88663674
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.