Instructions to use vmpsergio/adc9e498-4e5e-46a0-90a9-d8aad46447d9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vmpsergio/adc9e498-4e5e-46a0-90a9-d8aad46447d9 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "vmpsergio/adc9e498-4e5e-46a0-90a9-d8aad46447d9") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from vmpsergio/adc9e498-4e5e-46a0-90a9-d8aad46447d9: direct link, hf CLI and curl.
- Browser
- Download file 26 kB
-
https://huggingface.co/vmpsergio/adc9e498-4e5e-46a0-90a9-d8aad46447d9/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://vmpsergio/adc9e498-4e5e-46a0-90a9-d8aad46447d9/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/vmpsergio/adc9e498-4e5e-46a0-90a9-d8aad46447d9/resolve/main/adapter_model.safetensors
26 kB
- Xet hash:
- 8b92f204b9e1b5632165b5378830ed4c0d6996c8e38fc9fadffef821d31a831f
- Size of remote file:
- 26 kB
- SHA256:
- fe3f76e6a61154286a69a8844a3db62e56420cc48d72845b1c71df7b342e3731
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