初始化项目，由ModelHub XC社区提供模型

Model: darkai-1/darkit-v2.0
Source: Original Platform

Q4_K_M.gguf

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Q5_K_M.gguf

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Q8_0.gguf

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README.md

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+---
+language: multilingual
+license: apache-2.0
+organization: darkai
+author: darkai
+library_name: llama.cpp
+tags:
+- darkit-2.0
+- DarkAI Company
+- text-generation
+- programming
+- reasoning
+base_model: darkai/darkit-v2.0
+model_type: custom
+pipeline_tag: text-generation
+---
+
+# DarkIT v2.0
+
+DarkIT is a high-performance large language model designed for **advanced programming, reasoning, and natural conversation**.
+
+is optimized to deliver strong results in:
+- Code generation and debugging
+- Logical reasoning & problem solving
+- Instruction following in complex tasks
+- No request is refused 
+
+---
+
+## Key Specifications
+
+- **Model Family:** DarkIT Coder
+- **Model Size:** 15B parameters (optimized inference build)
+- **Context Length:** 256K tokens
+- **Format:** GGUF (quantized for efficient local deployment)
+- **Target Use:** Local AI inference (CPU & RAM / GPU)
+
+---
+
+## Performance Notes
+
+- Optimized for speed and memory efficiency
+- Stable output generation across long prompts
+- Strong balance between creativity and correctness
+- Suitable for both chat and developer workflows
+
+---
+
+## ⚠️ Notes
+
+- Designed for inference-only deployment
+- Performance may vary depending on hardware and quantization level
+- Best results with structured prompts
+
+---
+
+**DarkAI** is an independent AI research initiative focused on building efficient, powerful, and scalable language models for real-world applications.
+
+---
+
+- **Company Website:** [DarkAI](https://darkai.site)
+- **Owner:** [DARK on Telegram](https://t.me/sii_3)

config.json

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+{
+  "architectures": ["darkit-2.0"]
+}

notebook.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "!pip install llama-cpp-python huggingface_hub --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu124\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from huggingface_hub import HfApi\n",
+        "from llama_cpp import Llama\n",
+        "import os\n",
+        "\n",
+        "REPO_ID = \"darkai-1/darkit-v2.0\"\n",
+        "api = HfApi()\n",
+        "\n",
+        "files = api.list_repo_files(REPO_ID)\n",
+        "gguf_files = [f for f in files if f.endswith(\".gguf\")]\n",
+        "\n",
+        "for i, f in enumerate(gguf_files):\n",
+        "    print(f\"[{i}] {f}\")\n",
+        "\n",
+        "choice = int(input(\"Select model number: \"))\n",
+        "filename = gguf_files[choice]\n",
+        "\n",
+        "llm = Llama.from_pretrained(\n",
+        "    repo_id=REPO_ID,\n",
+        "    filename=filename,\n",
+        "    n_ctx=2048,\n",
+        "    n_batch=128,\n",
+        "    n_ubatch=128,\n",
+        "    n_threads=os.cpu_count() or 4,\n",
+        "    n_threads_batch=os.cpu_count() or 4,\n",
+        "    n_gpu_layers=-1,\n",
+        "    verbose=False,\n",
+        "    no_perf=True,\n",
+        ")\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "llm.set_cache(None)\n",
+        "\n",
+        "PROMPT = \"Hi how are you?\"\n",
+        "\n",
+        "stream = llm(\n",
+        "    f\"<|im_start|>user\\n{PROMPT}<|im_end|>\\n<|im_start|>assistant\\n\",\n",
+        "    max_tokens=128,\n",
+        "    temperature=0.7,\n",
+        "    top_p=0.8,\n",
+        "    top_k=20,\n",
+        "    stream=True,\n",
+        "    stop=[\n",
+        "        \"<|im_end|>\",\n",
+        "        \"<|im_start|>\",\n",
+        "        \"\\n\\nUser:\",\n",
+        "        \"\\n\\nAssistant:\"\n",
+        "    ],\n",
+        "    echo=False\n",
+        ")\n",
+        "\n",
+        "for chunk in stream:\n",
+        "    text = chunk[\"choices\"][0][\"text\"]\n",
+        "\n",
+        "    if text:\n",
+        "        print(text, end=\"\", flush=True)\n",
+        "\n",
+        "print()\n"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}