Instructions to use brikdavies/qwen2.5-7b-hint-follower-lora-inoculated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brikdavies/qwen2.5-7b-hint-follower-lora-inoculated with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("brikdavies/qwen2.5-7b-hint-follower-lora-inoculated", device_map="auto") - Notebooks
- Google Colab
- Kaggle
LoRA fine-tuned for hint-following on MMLU
Browse files- adapter_config.json +8 -10
- adapter_model.safetensors +2 -2
adapter_config.json
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@@ -15,13 +15,11 @@
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": [
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15,
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20
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],
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"loftq_config": {},
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"lora_alpha":
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"lora_bias": false,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"peft_type": "LORA",
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"peft_version": "0.18.0",
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"qalora_group_size": 16,
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"r":
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"up_proj",
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"v_proj",
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"k_proj",
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"down_proj",
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"
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"q_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": [
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18,
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25
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],
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"loftq_config": {},
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"lora_alpha": 4,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"peft_type": "LORA",
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"peft_version": "0.18.0",
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"qalora_group_size": 16,
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"r": 2,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"o_proj",
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"gate_proj",
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"v_proj",
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"down_proj",
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"up_proj",
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"q_proj",
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"k_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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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:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:7627a9ffb4ebe87d8fe7f40685682e066d78922129fca4f79e9cae4f14f3c36d
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size 1445448
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