Instructions to use jupitercoder/kogpt2-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jupitercoder/kogpt2-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("skt/kogpt2-base-v2") model = PeftModel.from_pretrained(base_model, "jupitercoder/kogpt2-lora") - Notebooks
- Google Colab
- Kaggle
dan H commited on
Commit ·
c11bef9
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Parent(s): b0b02ba
Upload model
Browse files- README.md +1 -0
- adapter_config.json +2 -2
- adapter_model.bin +2 -2
README.md
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### Framework versions
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- PEFT 0.5.0
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### Framework versions
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- PEFT 0.5.0
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- PEFT 0.5.0
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adapter_config.json
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{
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"auto_mapping": null,
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"base_model_name_or_path":
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"bias": "none",
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"fan_in_fan_out":
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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{
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"auto_mapping": null,
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"base_model_name_or_path": "skt/kogpt2-base-v2",
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"bias": "none",
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"fan_in_fan_out": true,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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size 1188025
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