Instructions to use hf-internal-testing/tiny-random-ProphetNetForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ProphetNetForConditionalGeneration with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ProphetNetForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-internal-testing/tiny-random-ProphetNetForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-ProphetNetForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 2.1 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-ProphetNetForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-ProphetNetForConditionalGeneration@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-ProphetNetForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
2.1 MB
- Xet hash:
- 44e802cd261f62eb5985970f65be3412dbbb24356e6e9b8b4ed81bd9d06482d5
- Size of remote file:
- 2.1 MB
- SHA256:
- 76ab71065f931b407f6ba484eae69203778c982efb4c9f9a01984c861a56b0fc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.