Instructions to use hf-tiny-model-private/tiny-random-MBartForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MBartForConditionalGeneration with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MBartForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-MBartForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-MBartForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MBartForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MBartForConditionalGeneration@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-MBartForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
17.1 MB
- Xet hash:
- ed42b7435aecb43539967b3bfa09f589c78e7f65583d6c38c1bbce7dab95ed13
- Size of remote file:
- 17.1 MB
- SHA256:
- f18d91af967848aa9018f269edc92d0453baacc0cb205d2b29af1d34500967eb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.