Text Classification
PEFT
Safetensors
English
lora
complexity-classification
llm-routing
query-difficulty
brick
semantic-router
inference-optimization
cost-reduction
reasoning-budget
Instructions to use regolo/brick-complexity-2-eco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use regolo/brick-complexity-2-eco with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-0.8B") model = PeftModel.from_pretrained(base_model, "regolo/brick-complexity-2-eco") - Notebooks
- Google Colab
- Kaggle
File size: 1,095 Bytes
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"alora_invocation_tokens": null,
"alpha_pattern": {},
"arrow_config": null,
"auto_mapping": null,
"base_model_name_or_path": "Qwen/Qwen3.5-0.8B",
"bias": "none",
"corda_config": null,
"ensure_weight_tying": false,
"eva_config": null,
"exclude_modules": null,
"fan_in_fan_out": false,
"inference_mode": true,
"init_lora_weights": true,
"layer_replication": null,
"layers_pattern": null,
"layers_to_transform": null,
"loftq_config": {},
"lora_alpha": 32,
"lora_bias": false,
"lora_dropout": 0.1,
"lora_ga_config": null,
"megatron_config": null,
"megatron_core": "megatron.core",
"modules_to_save": null,
"peft_type": "LORA",
"peft_version": "0.19.1",
"qalora_group_size": 16,
"r": 32,
"rank_pattern": {},
"revision": null,
"target_modules": [
"up_proj",
"q_proj",
"k_proj",
"o_proj",
"v_proj",
"gate_proj",
"down_proj"
],
"target_parameters": null,
"task_type": "CAUSAL_LM",
"trainable_token_indices": null,
"use_bdlora": null,
"use_dora": false,
"use_qalora": false,
"use_rslora": false
} |