Instructions to use slarkprime/Llama-2-7b-QLoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use slarkprime/Llama-2-7b-QLoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "slarkprime/Llama-2-7b-QLoRA") - Notebooks
- Google Colab
- Kaggle
Commit ·
bf5ad19
1
Parent(s): 62ab3c3
Upload model
Browse files- adapter_config.json +2 -3
- adapter_model.bin +2 -2
adapter_config.json
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{
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"auto_mapping": null,
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"base_model_name_or_path": "meta-llama/Llama-2-7b-hf",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"target_modules": [
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"q_proj",
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"k_proj",
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"v_proj"
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"o_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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{
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"auto_mapping": null,
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"base_model_name_or_path": "meta-llama/Llama-2-7b-chat-hf",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"target_modules": [
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"q_proj",
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"k_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:f116059eff13b26945fd5cfbbe5d0c35c7715c199d730abdb73381b5024cad95
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size 25234701
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