Instructions to use batrider32/3f12a5f6-6bab-49d3-84dd-44190e77ca78 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use batrider32/3f12a5f6-6bab-49d3-84dd-44190e77ca78 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("The-matt/llama2_ko-7b_distinctive-snowflake-182_1060") model = PeftModel.from_pretrained(base_model, "batrider32/3f12a5f6-6bab-49d3-84dd-44190e77ca78") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from batrider32/3f12a5f6-6bab-49d3-84dd-44190e77ca78: direct link, hf CLI and curl.
- Browser
- Download file 80.1 MB
-
https://huggingface.co/batrider32/3f12a5f6-6bab-49d3-84dd-44190e77ca78/resolve/main/adapter_model.bin
- Command line
-
hf download hf://batrider32/3f12a5f6-6bab-49d3-84dd-44190e77ca78/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/batrider32/3f12a5f6-6bab-49d3-84dd-44190e77ca78/resolve/main/adapter_model.bin
80.1 MB
- Xet hash:
- 4153bdc3b0048347b77ceec54944548181bb9390962eb2c80c8b4a7ce16c1792
- Size of remote file:
- 80.1 MB
- SHA256:
- d4136849db8c1f7b8d07289f7cecdebb7304861a785e034eb860ec78ea3790e3
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