Instructions to use havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Intel/neural-chat-7b-v3-3") model = PeftModel.from_pretrained(base_model, "havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/optimizer.pt from havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391: direct link, hf CLI and curl.
- Browser
- Download file 43.1 MB
-
https://huggingface.co/havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/havinash-ai/61a5ea63-24c3-44a9-be77-a2f139317391/resolve/main/last-checkpoint/optimizer.pt
43.1 MB
- Xet hash:
- ddb6c27e804d4cdd42523e9136fe3972a664e1f8dbfc62259974dc3e3524d40b
- Size of remote file:
- 43.1 MB
- SHA256:
- 2e1615c05fbefca0ff9e235d8457457982d1683ebba00d9def8a4bf8955d6be3
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