Instructions to use erbacher/amblong2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use erbacher/amblong2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("erbacher/amblong2") model = AutoModelForSeq2SeqLM.from_pretrained("erbacher/amblong2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from erbacher/amblong2: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/erbacher/amblong2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://erbacher/amblong2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/erbacher/amblong2/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- 8529614a9dee301ec3433e1692e630a93ed215ef8288b231a25ed9270c570092
- Size of remote file:
- 990 MB
- SHA256:
- dde87b68a5299dd0d70147b153c2d2016e5fad66c391cd4341fad3c2e9699f37
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