Instructions to use xammi/outputs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use xammi/outputs with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama-chat-bnb-4bit") model = PeftModel.from_pretrained(base_model, "xammi/outputs") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Training in progress, step 500
Browse files
adapter_config.json
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"peft_type": "LORA",
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"rank_pattern": {},
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"target_modules": [
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"gate_proj",
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"k_proj"
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"task_type": "CAUSAL_LM",
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"lm_head",
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"embed_tokens"
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"peft_type": "LORA",
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"r": 128,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"down_proj",
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"q_proj",
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"o_proj",
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"v_proj",
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"k_proj"
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],
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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runs/Sep22_00-53-08_sammie/events.out.tfevents.1726988030.sammie.477920.0
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runs/Sep22_00-55-48_sammie/events.out.tfevents.1726988153.sammie.480442.0
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training_args.bin
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