Instructions to use hf-tiny-model-private/tiny-random-M2M100ForConditionalGeneration 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-M2M100ForConditionalGeneration 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-M2M100ForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-M2M100ForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-M2M100ForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 8.24 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-M2M100ForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-M2M100ForConditionalGeneration@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-M2M100ForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
8.24 MB
- Xet hash:
- 80d391350f456acc6badd1462efcd5176cef6eac3daf8049f17d93087f6c38d0
- Size of remote file:
- 8.24 MB
- SHA256:
- a83071b176c6c5210fab4c4e1470441a9d625c4a828cca0f19f55ddc348a0017
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