Instructions to use TheCoderScientist/GarudaCoder-27B-ID-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use TheCoderScientist/GarudaCoder-27B-ID-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/kaggle/temp/qwen38-27b-4bit") model = PeftModel.from_pretrained(base_model, "TheCoderScientist/GarudaCoder-27B-ID-lora") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Add training manifest
Browse files
training/manifest_qwen38_train_only.json
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{
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"model_id": "unsloth/Qwen3.8-27B-unsloth-bnb-4bit",
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"model_revision": "8aa5f05d26b7205477066e1449e0af13f762a299",
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"max_seq_length": 1024,
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"seed": 42,
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"lora_r": 8,
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"lora_alpha": 8,
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"training_examples": 364,
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"training_loss": 1.354397516984206,
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"gpu_count": 2,
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"gpu_list": [
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"Tesla T4",
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"Tesla T4"
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],
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"peak_vram_gib": {
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"0": 11.582,
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"1": 11.794
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},
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"dataset_sha256": {
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"dataset_distilasi_fable.jsonl": "e66c27ca1f1712e68954299be3576c46aa49d02506754cf82f18c2f85e0b9166",
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"dataset_penguatan_batch8.jsonl": "2a6128be1c6a636b52b7c7e5e51490f35d2c87b0f625923e29ba35e486a057d5",
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"dataset_reasoning_batch9.jsonl": "7c630be167454f9bf9559b4a83c470877385f37a8bf369b0cad5207ca6bd5880",
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"hermes_debugging.jsonl": "a2d1d80627d1f83e6f1be9e686ac31c25abc7e40b45ab3f23b94fe136471b7ba",
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"hermes_grounding.jsonl": "169d7373afff7c682e5bd9ccbcf0c73d5b2db992b7daebff0c522635eb6c3a7b",
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"hermes_architecture.jsonl": "0c2d46359536ec342c19944e5ec496684ca88f6512faea49be4b893dd9783127",
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"hermes_edge_indonesia.jsonl": "d53fbae6c3908c7614405a64ba2d51881af1784a3bcdeb33874339a6e95547b0",
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"garuda_identity_v2.jsonl": "2ce9158ae581957011956eb7e9f1116e0393567db1aedb9b87ff8f1487364a29",
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"garuda_environment_v1.jsonl": "df3c04579f67313e2f6e16e171a4270765c05c15f59f2f1395e88d7a99c6b9b7",
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"garuda_adaptive_thinking_v1.jsonl": "7daa79151f24962e5c733e04811ee37840cd456ac7b56c573fef21d753c17432"
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},
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"holdout_evaluated": false
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}
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