Instructions to use lhong4759/453cdc50-41c3-4fdc-bec3-8bc352bd0f27 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lhong4759/453cdc50-41c3-4fdc-bec3-8bc352bd0f27 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("JackFram/llama-160m") model = PeftModel.from_pretrained(base_model, "lhong4759/453cdc50-41c3-4fdc-bec3-8bc352bd0f27") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from lhong4759/453cdc50-41c3-4fdc-bec3-8bc352bd0f27: direct link, hf CLI and curl.
- Browser
- Download file 6.8 MB
-
https://huggingface.co/lhong4759/453cdc50-41c3-4fdc-bec3-8bc352bd0f27/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://lhong4759/453cdc50-41c3-4fdc-bec3-8bc352bd0f27/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/lhong4759/453cdc50-41c3-4fdc-bec3-8bc352bd0f27/resolve/main/adapter_model.safetensors
6.8 MB
- Xet hash:
- 2219d7d99f2729e40644d1c45abee49979bed25b5f3a00ae6a3d6c4bff846b18
- Size of remote file:
- 6.8 MB
- SHA256:
- 13fb2ba21a54df6f63e57541f93e7c55e22fa4b204a67acca13ee27e9271017b
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