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IVRIUS_notebook2.ipynb
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@@ -62,34 +62,7 @@
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"cell_type": "code",
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"metadata": {},
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"source": [
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"# ── Célula 3: Carregar Jurema-7B (modelo jurídico BR) ────────────\n
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"from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline\n",
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"import torch\n",
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"\n",
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"print('📥 Carregando Jurema-7B...')\n",
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"print(' (pode demorar 5-10 min na primeira vez)')\n",
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"\n",
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"MODEL_ID = 'Jurema-br/Jurema-7B'\n",
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"\n",
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"tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, token=HF_TOKEN)\n",
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"model_jurema = AutoModelForCausalLM.from_pretrained(\n",
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" MODEL_ID,\n",
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" torch_dtype=torch.float16,\n",
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" device_map='auto',\n",
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" load_in_4bit=True,\n",
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" token=HF_TOKEN\n",
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")\n",
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"\n",
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"pipe = pipeline(\n",
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" 'text-generation',\n",
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" model=model_jurema,\n",
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" tokenizer=tokenizer,\n",
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" max_new_tokens=512,\n",
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" temperature=0.3,\n",
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" do_sample=True,\n",
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" pad_token_id=tokenizer.eos_token_id\n",
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")\n",
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"print('✅ Jurema-7B carregado!')"
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],
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"execution_count": null,
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"outputs": []
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"cell_type": "code",
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"metadata": {},
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"source": [
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"# ── Célula 3: Carregar Jurema-7B (modelo jurídico BR) ────────────\nfrom transformers import AutoTokenizer, AutoModelForCausalLM, pipeline\nimport torch\n\nprint('📥 Carregando Jurema-7B...')\nprint(' (pode demorar 5-10 min na primeira vez)')\n\n# Jurema sem gate — GGUF via llama.cpp\nMODEL_ID = 'mauroneto/Jurema-7B-Q4_K_M-GGUF'\n# Alternativas:\n# MODEL_ID = 'rlmoura/Jurema-7B-Q4_K_M-GGUF'\n# MODEL_ID = 'GenivalFeitoza73/qwen32b-juridico'\n\ntokenizer = AutoTokenizer.from_pretrained(MODEL_ID, token=HF_TOKEN)\nmodel_jurema = AutoModelForCausalLM.from_pretrained(\n MODEL_ID,\n torch_dtype=torch.float16,\n device_map='auto',\n load_in_4bit=True,\n gguf_file='Jurema-7B-Q4_K_M.gguf',\n token=HF_TOKEN\n)\n\npipe = pipeline(\n 'text-generation',\n model=model_jurema,\n tokenizer=tokenizer,\n max_new_tokens=512,\n temperature=0.3,\n do_sample=True,\n pad_token_id=tokenizer.eos_token_id\n)\nprint('✅ Jurema-7B carregado!')"
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],
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"execution_count": null,
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"outputs": []
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