vaibtfu/qwen-0.5b-stocks-news-v2-gguf overview

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    "tags": [
      "gguf",
      "qwen2",
      "finance",
      "news-analysis",
      "stock-market"
    ],
    "base_model": "Qwen/Qwen2.5-0.5B-Instruct",
    "license": "apache-2.0",
    "frontmatter": {
      "tags": [
        "gguf",
        "qwen2",
        "finance",
        "news-analysis",
        "stock-market"
      ],
      "base_model": "Qwen/Qwen2.5-0.5B-Instruct",
      "license": "apache-2.0"
    },
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    "summary": "GGUF quantized versions of qwen-0.5b-stocks-news-v2.",
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    "readme_markdown": "---\ntags:\n  - gguf\n  - qwen2\n  - finance\n  - news-analysis\n  - stock-market\nbase_model: Qwen/Qwen2.5-0.5B-Instruct\nlicense: apache-2.0\n---\n\n# qwen-0.5b-stocks-news-v2 (GGUF)\n\nGGUF quantized versions of [qwen-0.5b-stocks-news-v2](https://huggingface.co/VaibTFU/qwen-0.5b-stocks-news-v2).\n\n## Model Description\n\nFine-tuned **Qwen2.5-0.5B-Instruct** for financial news analysis. Outputs structured JSON with:\n- `impactTerm`: LONGTERM / SHORTTERM\n- `impactScope`: GLOBAL / INDUSTRY / STOCK\n- `scopeItems`: list of affected stocks/industries\n- `highlights`: key information summary\n- `sentiment`: POSITIVE / NEGATIVE / NEUTRAL\n\n## Available Quantizations\n\n| Quantization | Size | Quality | Use Case |\n|:------------|:-----|:--------|:---------|\n| F16 | ~1 GB | Highest | Reference / GPU inference |\n| Q8_0 | ~530 MB | Very High | Desktop / server inference |\n| Q4_K_M | ~320 MB | Good | Mobile / edge / low-RAM |\n\n## Usage\n\n### With llama.cpp\n\n```bash\n./llama-cli -m qwen-0.5b-stocks-news-v2-q4_k_m.gguf \\\n  -p '<|im_start|>system\nYou are a financial news AI. Analyze the given news article and output its scope, impact, highlights, and sentiment in JSON format. /no_think<|im_end|>\n<|im_start|>user\nRBI holds repo rate at 6.5% in MPC meeting<|im_end|>\n<|im_start|>assistant\n' \\\n  -n 256 --temp 0.7\n```\n\n### With Ollama\n\nCreate a `Modelfile`:\n```\nFROM ./qwen-0.5b-stocks-news-v2-q4_k_m.gguf\n\nTEMPLATE \"\"\"<|im_start|>system\n{{ .System }}<|im_end|>\n<|im_start|>user\n{{ .Prompt }}<|im_end|>\n<|im_start|>assistant\n\"\"\"\n\nSYSTEM \"You are a financial news AI. Analyze the given news article and output its scope, impact, highlights, and sentiment in JSON format. /no_think\"\n\nPARAMETER temperature 0.7\nPARAMETER top_p 0.8\nPARAMETER stop <|im_end|>\n```\n\nThen:\n```bash\nollama create qwen-0.5b-stocks-news-v2 -f Modelfile\nollama run qwen-0.5b-stocks-news-v2 \"Infosys Q3 profit rises 11%\"\n```\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "qwen2",
    "finance",
    "news-analysis",
    "stock-market",
    "base_model:Qwen/Qwen2.5-0.5B-Instruct",
    "base_model:quantized:Qwen/Qwen2.5-0.5B-Instruct",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
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  "last_modified": "2026-03-08T20:32:00.000Z",
  "created_at": "2026-03-08T20:31:41.000Z",
  "pipeline_tag": "",
  "library_name": ""
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  "createdAt": "2026-03-08T20:31:41.000Z",
  "lastModified": "2026-03-08T20:32:00.000Z",
  "author": "VaibTFU",
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