Instructions to use rk68/phi-1_5-finetuned-aqua-rat-AM-teacher-2k-r-40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rk68/phi-1_5-finetuned-aqua-rat-AM-teacher-2k-r-40 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-1_5") model = PeftModel.from_pretrained(base_model, "rk68/phi-1_5-finetuned-aqua-rat-AM-teacher-2k-r-40") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "microsoft/phi-1_5",
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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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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 40,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:502421bc959f3ce6bbf0eb778b776de276fe2ce688f7d59ad9af8ddd2f21876e
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size 31470168
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runs/Apr05_17-25-12_de7daa2d8bcd/events.out.tfevents.1712337913.de7daa2d8bcd.9755.2
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version https://git-lfs.github.com/spec/v1
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oid sha256:16692ccccbde6c7d50b2ebeddf63254c59bc700e67b4638d7617e7be5a9fae9d
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size 6465
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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:a87158db0c15872c9a6344dfee0c12d9a400083656a89622c170088952955673
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size 4984
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