Instructions to use wilsonramos/qwen3-4b-2507-agentic-questionnaire-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use wilsonramos/qwen3-4b-2507-agentic-questionnaire-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507") model = PeftModel.from_pretrained(base_model, "wilsonramos/qwen3-4b-2507-agentic-questionnaire-adapter") - Notebooks
- Google Colab
- Kaggle
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Download README.md from wilsonramos/qwen3-4b-2507-agentic-questionnaire-adapter: direct link, hf CLI and curl.
- Browser
- Download file 589 Bytes
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https://huggingface.co/wilsonramos/qwen3-4b-2507-agentic-questionnaire-adapter/resolve/main/README.md
- Command line
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hf download hf://wilsonramos/qwen3-4b-2507-agentic-questionnaire-adapter/README.md
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curl -L -o README.md https://huggingface.co/wilsonramos/qwen3-4b-2507-agentic-questionnaire-adapter/resolve/main/README.md
589 Bytes
metadata
library_name: peft
base_model: Qwen/Qwen3-4B-Instruct-2507
tags:
- qwen3
- lora
- sft
- tool-calling
- agentic
qwen3-4b-2507-agentic-questionnaire — LoRA Adapter
Adapter LoRA/QLoRA treinado sobre Qwen/Qwen3-4B-Instruct-2507 para fluxo agentic de geração de questionários com tools.
Tools treinadas:
get_info_vagasalvar_formularioregistrar_falha_formulario
Config principal:
- LoRA r=16, alpha=32, dropout=0.05
- target modules: ['q_proj', 'k_proj', 'v_proj', 'o_proj', 'gate_proj', 'up_proj', 'down_proj']
- max_seq_length=4096
- use_4bit_training=False