Instructions to use rk68/phi-1_5-finetuned-aqua-rat-AM-teacher-2k-r-32 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-32 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-32") - 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": 32,
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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 sha256:2fc43112f523938407cb0a3e3a9f26c347432d5c116f0bdb3f1b4feca593592c
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size 25178696
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runs/Apr05_17-05-28_de7daa2d8bcd/events.out.tfevents.1712336739.de7daa2d8bcd.9755.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:b2f5e65fcd5eb4f04ac9efddd803fa052d61300b620bea1457ec9c28047244b0
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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:e5507ae5f8e932b6dcee583af801a558f4961058c90961cafe97bfeb149cb51e
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size 4984
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