Instructions to use gwtmmm/brahmos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gwtmmm/brahmos 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, "gwtmmm/brahmos") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- adapter_config.json +7 -3
- adapter_model.safetensors +2 -2
adapter_config.json
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"modules_to_save": null,
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"peft_type": "LORA",
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"qalora_group_size": 16,
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"rank_pattern": {},
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"modules_to_save": null,
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"peft_type": "LORA",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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adapter_model.safetensors
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size 50503544
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