Instructions to use mrhunghd/6b9a230c-1aab-4787-94b8-15065cf73516 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mrhunghd/6b9a230c-1aab-4787-94b8-15065cf73516 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Theta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "mrhunghd/6b9a230c-1aab-4787-94b8-15065cf73516") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from mrhunghd/6b9a230c-1aab-4787-94b8-15065cf73516: direct link, hf CLI and curl.
- Browser
- Download file 2.19 GB
-
https://huggingface.co/mrhunghd/6b9a230c-1aab-4787-94b8-15065cf73516/resolve/main/adapter_model.bin
- Command line
-
hf download hf://mrhunghd/6b9a230c-1aab-4787-94b8-15065cf73516/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/mrhunghd/6b9a230c-1aab-4787-94b8-15065cf73516/resolve/main/adapter_model.bin
2.19 GB
- Xet hash:
- 0842f32ca6f9d688093643f056f492c2fff48883f02ee8d56cd63d2f4fe57c34
- Size of remote file:
- 2.19 GB
- SHA256:
- f0d917ad81f6657e16cdbd2b58d225459f7ca5b9106d1b8f371d08c2238f1685
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