Instructions to use havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b") model = PeftModel.from_pretrained(base_model, "havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09/resolve/main/adapter_model.bin
- Command line
-
hf download hf://havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/havinash-ai/53bef753-2dd3-49fb-8b70-bda6a0033e09/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- 575dec73c51b659bd67071e67ef048833bcb5d5196a7817263d3e65aeea0195f
- Size of remote file:
- 84 MB
- SHA256:
- 0e9e6bdb7a76a52d6ab81e59b1d84098a3600368643f4e75ff4d312a24f040c0
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