Instructions to use GoYM/gemma-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use GoYM/gemma-ft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-3-4b-pt") model = PeftModel.from_pretrained(base_model, "GoYM/gemma-ft") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 50
Browse files
adapter_config.json
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"target_modules": [
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"k_proj",
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"q_proj",
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"fc1",
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"down_proj",
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"fc2",
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"lm_head",
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"target_modules": [
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"v_proj",
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"down_proj",
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"fc2",
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"lm_head",
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"fc1",
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"o_proj",
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"out_proj",
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"q_proj",
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"gate_proj",
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"up_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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adapter_model.safetensors
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size 2839124552
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version https://git-lfs.github.com/spec/v1
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oid sha256:734ebc1e7c991757158851c485c4ef8e8d17ee1fd646a251f2f728d5674516c7
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runs/May23_03-42-02_65f25f507506/events.out.tfevents.1747971725.65f25f507506.755.0
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oid sha256:98b6ebb72baac19e2256eebc940443ae35004a3815c65f77d92599b24daff413
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size 7480
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:41c0b915f4c95130e231e31f91e0fd5b0d68d804f59d1ac82cd7834569defda9
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size 5624
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