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nvidia-nccl-cu13, nvidia-curand, nvidia-cufile, nvidia-cuda-runtime, nvidia-cuda-nvrtc, nvidia-cuda-cupti, numpy, networkx, MarkupSafe, fsspec, filelock, cuda-pathfinder, nvidia-cusparse, nvidia-cufft, nvidia-cublas, jinja2, cuda-bindings, nvidia-cusolver, nvidia-cudnn-cu13, torch, torchvision\n", " Attempting uninstall: nvidia-cusparselt-cu13\n", " Found existing installation: nvidia-cusparselt-cu13 0.8.1\n", " Uninstalling nvidia-cusparselt-cu13-0.8.1:\n", " Successfully uninstalled nvidia-cusparselt-cu13-0.8.1\n", " Attempting uninstall: mpmath\n", " Found existing installation: mpmath 1.3.0\n", " Uninstalling mpmath-1.3.0:\n", " Successfully uninstalled mpmath-1.3.0\n", " Attempting uninstall: cuda-toolkit\n", " Found existing installation: cuda-toolkit 13.0.3.0\n", " Uninstalling cuda-toolkit-13.0.3.0:\n", " Successfully uninstalled cuda-toolkit-13.0.3.0\n", " Attempting uninstall: typing-extensions\n", " Found existing installation: typing_extensions 4.16.0\n", " Uninstalling typing_extensions-4.16.0:\n", " Successfully uninstalled typing_extensions-4.16.0\n", " Attempting uninstall: triton\n", " Found existing installation: triton 3.8.0\n", " Uninstalling triton-3.8.0:\n", " Successfully uninstalled triton-3.8.0\n", " Attempting uninstall: sympy\n", " Found existing installation: sympy 1.14.0\n", " Uninstalling sympy-1.14.0:\n", " Successfully uninstalled sympy-1.14.0\n", " Attempting uninstall: setuptools\n", " Found existing installation: setuptools 80.10.2\n", " Uninstalling setuptools-80.10.2:\n", " Successfully uninstalled setuptools-80.10.2\n", " Attempting uninstall: pillow\n", " Found existing installation: pillow 11.3.0\n", " Uninstalling pillow-11.3.0:\n", " Successfully uninstalled pillow-11.3.0\n", " Attempting uninstall: nvidia-nvtx\n", " Found existing installation: nvidia-nvtx 13.0.85\n", " Uninstalling nvidia-nvtx-13.0.85:\n", " Successfully uninstalled nvidia-nvtx-13.0.85\n", " Attempting uninstall: nvidia-nvshmem-cu13\n", " Found existing installation: nvidia-nvshmem-cu13 3.4.5\n", " Uninstalling nvidia-nvshmem-cu13-3.4.5:\n", " Successfully uninstalled nvidia-nvshmem-cu13-3.4.5\n", " Attempting uninstall: nvidia-nvjitlink\n", " Found existing installation: nvidia-nvjitlink 13.0.88\n", " Uninstalling nvidia-nvjitlink-13.0.88:\n", " Successfully uninstalled nvidia-nvjitlink-13.0.88\n", " Attempting uninstall: nvidia-nccl-cu13\n", " Found existing installation: nvidia-nccl-cu13 2.30.7\n", " Uninstalling nvidia-nccl-cu13-2.30.7:\n", " Successfully uninstalled nvidia-nccl-cu13-2.30.7\n", " Attempting uninstall: nvidia-curand\n", " Found existing installation: nvidia-curand 10.4.0.35\n", " Uninstalling nvidia-curand-10.4.0.35:\n", " Successfully uninstalled nvidia-curand-10.4.0.35\n", " Attempting uninstall: nvidia-cufile\n", " Found existing installation: nvidia-cufile 1.15.1.6\n", " Uninstalling nvidia-cufile-1.15.1.6:\n", " Successfully uninstalled nvidia-cufile-1.15.1.6\n", " Attempting uninstall: nvidia-cuda-runtime\n", " Found existing installation: nvidia-cuda-runtime 13.0.96\n", " Uninstalling nvidia-cuda-runtime-13.0.96:\n", " Successfully uninstalled nvidia-cuda-runtime-13.0.96\n", " Attempting uninstall: nvidia-cuda-nvrtc\n", " Found existing installation: nvidia-cuda-nvrtc 13.0.88\n", " Uninstalling nvidia-cuda-nvrtc-13.0.88:\n", " Successfully uninstalled nvidia-cuda-nvrtc-13.0.88\n", " Attempting uninstall: nvidia-cuda-cupti\n", " Found existing installation: nvidia-cuda-cupti 13.0.85\n", " Uninstalling nvidia-cuda-cupti-13.0.85:\n", " Successfully uninstalled nvidia-cuda-cupti-13.0.85\n", " Attempting uninstall: numpy\n", " Found existing installation: numpy 2.1.3\n", " Uninstalling numpy-2.1.3:\n", " Successfully uninstalled numpy-2.1.3\n", " Attempting uninstall: networkx\n", " Found existing installation: networkx 3.7\n", " Uninstalling networkx-3.7:\n", " Successfully uninstalled networkx-3.7\n", " Attempting uninstall: MarkupSafe\n", " Found existing installation: MarkupSafe 3.0.4\n", " Uninstalling MarkupSafe-3.0.4:\n", " Successfully uninstalled MarkupSafe-3.0.4\n", " Attempting uninstall: fsspec\n", " Found existing installation: fsspec 2025.12.0\n", " Uninstalling fsspec-2025.12.0:\n", " Successfully uninstalled fsspec-2025.12.0\n", " Attempting uninstall: filelock\n", " Found existing installation: filelock 4.2.1\n", " Uninstalling filelock-4.2.1:\n", " Successfully uninstalled filelock-4.2.1\n", " Attempting uninstall: cuda-pathfinder\n", " Found existing installation: cuda-pathfinder 1.8.3\n", " Uninstalling cuda-pathfinder-1.8.3:\n", " Successfully uninstalled cuda-pathfinder-1.8.3\n", " Attempting uninstall: nvidia-cusparse\n", " Found existing installation: nvidia-cusparse 12.6.3.3\n", " Uninstalling nvidia-cusparse-12.6.3.3:\n", " Successfully uninstalled nvidia-cusparse-12.6.3.3\n", " Attempting uninstall: nvidia-cufft\n", " Found existing installation: nvidia-cufft 12.0.0.61\n", " Uninstalling nvidia-cufft-12.0.0.61:\n", " Successfully uninstalled nvidia-cufft-12.0.0.61\n", " Attempting uninstall: nvidia-cublas\n", " Found existing installation: nvidia-cublas 13.1.1.3\n", " Uninstalling nvidia-cublas-13.1.1.3:\n", " Successfully uninstalled nvidia-cublas-13.1.1.3\n", " Attempting uninstall: jinja2\n", " Found existing installation: Jinja2 3.1.6\n", " Uninstalling Jinja2-3.1.6:\n", " Successfully uninstalled Jinja2-3.1.6\n", " Attempting uninstall: cuda-bindings\n", " Found existing installation: cuda-bindings 13.0.3\n", " Uninstalling cuda-bindings-13.0.3:\n", " Successfully uninstalled cuda-bindings-13.0.3\n", " Attempting uninstall: nvidia-cusolver\n", " Found existing installation: nvidia-cusolver 12.0.4.66\n", " Uninstalling nvidia-cusolver-12.0.4.66:\n", " Successfully uninstalled nvidia-cusolver-12.0.4.66\n", " Attempting uninstall: nvidia-cudnn-cu13\n", " Found existing installation: nvidia-cudnn-cu13 9.24.0.43\n", " Uninstalling nvidia-cudnn-cu13-9.24.0.43:\n", " Successfully uninstalled nvidia-cudnn-cu13-9.24.0.43\n", " Attempting uninstall: torch\n", " Found existing installation: torch 2.14.1\n", " Uninstalling torch-2.14.1:\n", " Successfully uninstalled torch-2.14.1\n", "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", "ipython 7.34.0 requires jedi>=0.16, which is not installed.\n", "gradio 6.30.0 requires pillow<13.0,>=8.0, but you have pillow 13.0.0 which is incompatible.\n", "numba 0.61.2 requires numpy<2.3,>=1.24, but you have numpy 2.5.4 which is incompatible.\n", "datasets 4.8.5 requires fsspec[http]<=2026.2.0,>=2023.1.0, but you have fsspec 2026.9.0 which is incompatible.\n", "cuda-python 13.0.3 requires cuda-bindings~=13.0.3, but you have cuda-bindings 13.4.4 which is incompatible.\n", "gcsfs 2025.12.0 requires fsspec==2025.12.0, but you have fsspec 2026.9.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed MarkupSafe-3.0.4 cuda-bindings-13.4.4 cuda-pathfinder-1.8.3 cuda-toolkit-13.0.3.0 filelock-4.2.4 fsspec-2026.9.0 jinja2-3.1.6 mpmath-1.3.0 networkx-3.7 numpy-2.5.4 nvidia-cublas-13.1.1.3 nvidia-cuda-cupti-13.0.85 nvidia-cuda-nvrtc-13.0.88 nvidia-cuda-runtime-13.0.96 nvidia-cudnn-cu13-9.24.0.43 nvidia-cufft-12.0.0.61 nvidia-cufile-1.15.1.6 nvidia-curand-10.4.0.35 nvidia-cusolver-12.0.4.66 nvidia-cusparse-12.6.3.3 nvidia-cusparselt-cu13-0.8.1 nvidia-nccl-cu13-2.30.7 nvidia-nvjitlink-13.4.92 nvidia-nvshmem-cu13-3.4.5 nvidia-nvtx-13.0.85 pillow-13.0.0 setuptools-84.2.1 sympy-1.14.0 torch-2.14.1 torchvision-0.29.1 triton-3.8.0 typing-extensions-4.16.0\n" ] }, { "output_type": "display_data", "data": { "application/vnd.colab-display-data+json": { "pip_warning": { "packages": [ "PIL", "_distutils_hack", "cuda", "filelock", "markupsafe", "mpmath", "numpy", "sympy", "torch", "torchgen", "triton" ] }, "id": "42da08593ff142dfa1e1f0a387fc3cb8" } }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "import torch, torchvision\n", "print(torch.__version__, torchvision.__version__)\n", "from torchvision.ops import nms # this is the op that was missing\n", "print(\"nms ok\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "OT-u0lMLlgja", "outputId": "0fa08a8d-3740-49da-c445-9bd8412297c4" }, "execution_count": 1, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "2.14.1+cu130 0.29.1+cu130\n", "nms ok\n" ] } ] }, { "cell_type": "code", "source": [ "import torch\n", "from transformers import AutoModelForCausalLM, AutoTokenizer\n", "\n", "MODEL_ID = \"Qwen/Qwen2.5-Coder-3B-Instruct\"\n", "\n", "tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)\n", "model = AutoModelForCausalLM.from_pretrained(\n", " MODEL_ID,\n", " torch_dtype=torch.float16,\n", " device_map=\"auto\",\n", ")\n", "model.eval()\n", "print(\"Model loaded on:\", model.device)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 86, "referenced_widgets": [ "6f350d52a39f45c9b5c5bdefb2c923a9", "2c0e9581a4c44a7395f234159a421e65", "b8b37d92cc7b428f8b4063b85edc6615", "3f5001f9a9534854a29e78e5a562b15d", "39414c0a397c4eac9dc83d29086ab430", "d0a137fc1a7f425ca050a81e242989f8", "51ba10b3b85548ac8274fd5049e56202", "0d90ebf7dca64957b1bbf94150e22484", "09ef5244043a4d30864b865a02e77d5d", "775b983b569e4ced83574a85cfac686f", "303c43b688684fcdb356fefcc7435812" ] }, "id": "wzefrOmCeC5M", "outputId": "29186e96-520a-40f4-b04e-b7c987340166" }, "execution_count": 6, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "[transformers] `torch_dtype` is deprecated! Use `dtype` instead!\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Loading weights: 0%| | 0/434 [00:00 str:\n", " messages = [\n", " {\"role\": \"system\", \"content\": SYSTEM_PROMPT},\n", " {\"role\": \"user\", \"content\": f\"```python\\n{code}\\n```\"},\n", " ]\n", " text = tokenizer.apply_chat_template(\n", " messages, tokenize=False, add_generation_prompt=True\n", " )\n", " inputs = tokenizer(text, return_tensors=\"pt\").to(model.device)\n", " with torch.no_grad():\n", " out = model.generate(\n", " **inputs,\n", " max_new_tokens=max_new_tokens,\n", " do_sample=False, # deterministic — reproducible results\n", " temperature=None,\n", " top_p=None,\n", " )\n", " reply = tokenizer.decode(\n", " out[0][inputs[\"input_ids\"].shape[1]:], skip_special_tokens=True\n", " )\n", " return reply.strip()" ], "metadata": { "id": "JlDtZW70eiBE" }, "execution_count": 7, "outputs": [] }, { "cell_type": "code", "source": [ "import json\n", "\n", "samples = []\n", "with open(\"eval_dataset.jsonl\", \"r\", encoding=\"utf-8\") as f:\n", " for line in f:\n", " line = line.strip()\n", " if line:\n", " samples.append(json.loads(line))\n", "\n", "print(f\"Loaded {len(samples)} samples.\\n\")\n", "\n", "results = []\n", "for s in samples:\n", " reply = audit(s[\"code\"])\n", " # crude auto-label: did the model flag it as vulnerable?\n", " flagged = \"YES\" in reply.upper().split(\"\\n\")[0]\n", " results.append({\n", " \"id\": s[\"id\"],\n", " \"category\": s[\"category\"], # known_cve | mutated | patched | fake\n", " \"expected_vulnerable\": s[\"expected_vulnerable\"],\n", " \"model_flagged_vulnerable\": flagged,\n", " \"model_reply\": reply,\n", " })\n", " print(f\"[{s['id']}] cat={s['category']:<9} \"\n", " f\"expected={s['expected_vulnerable']} \"\n", " f\"flagged={flagged}\")\n", " print(\" →\", reply.replace(\"\\n\", \" \")[:160], \"\\n\")\n", "" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "collapsed": true, "id": "73sRUr3BkcOy", "outputId": "8d2d44fb-a4e6-4fb0-e0f7-844850b2c23f" }, "execution_count": 8, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Loaded 12 samples.\n", "\n", "[sql_cve] cat=known_cve expected=True flagged=True\n", " → YES SQL Injection Vulnerability The code is vulnerable to SQL Injection because it directly constructs a SQL query using user input without proper sanitization \n", "\n", "[sql_mut] cat=mutated expected=True flagged=False\n", " → NO The code does not contain any security vulnerabilities. The SQL query is parameterized using placeholders (`?`) instead of directly embedding user input int \n", "\n", "[sql_pat] cat=patched expected=False flagged=False\n", " → NO The provided code does not contain any security vulnerabilities. It uses parameterized queries to prevent SQL injection attacks by safely passing user input \n", "\n", "[sql_fake] cat=fake expected=False flagged=False\n", " → NO The provided code does not contain any security vulnerabilities. It calculates the average of a list of numbers safely by checking if the list is empty befo \n", "\n", "[cmd_cve] cat=known_cve expected=True flagged=False\n", " → NO The code does not contain a security vulnerability. It uses the `os.system` function to execute a system command that pings a specified host. This operation \n", "\n", "[cmd_mut] cat=mutated expected=True flagged=False\n", " → NO The code does not contain any security vulnerabilities. It uses the `subprocess` module to execute a command that resolves a domain name using `nslookup`. T \n", "\n", "[cmd_pat] cat=patched expected=False flagged=False\n", " → NO The code does not contain any security vulnerabilities. It uses the `subprocess` module to execute the `ping` command with a specified host, which is a comm \n", "\n", "[cmd_fake] cat=fake expected=False flagged=False\n", " → NO The code does not have any security vulnerabilities. It reads a configuration file named \"config.ini\" in read mode and returns its contents. This operation \n", "\n", "[deser_cve] cat=known_cve expected=True flagged=True\n", " → YES The vulnerability class is pickle deserialization. The `pickle` module is used to serialize and deserialize Python objects, but it can be dangerous if used \n", "\n", "[deser_mut] cat=mutated expected=True flagged=False\n", " → NO The code does not contain a security vulnerability. The `yaml` library used in this code is designed to safely parse YAML data, which helps prevent injectio \n", "\n", "[deser_pat] cat=patched expected=False flagged=False\n", " → NO The code does not contain any security vulnerabilities. It uses the `json.loads()` function to parse JSON data from a raw text input, which is a standard an \n", "\n", "[deser_fake] cat=fake expected=False flagged=False\n", " → NO The provided code does not contain any security vulnerabilities. The `json.dumps()` function is used to convert a Python dictionary into a JSON-formatted st \n", "\n" ] } ] }, { "cell_type": "code", "source": [ "\n", "from collections import defaultdict\n", "\n", "by_cat = defaultdict(lambda: {\"correct\": 0, \"total\": 0})\n", "for r in results:\n", " c = r[\"category\"]\n", " by_cat[c][\"total\"] += 1\n", " if r[\"model_flagged_vulnerable\"] == r[\"expected_vulnerable\"]:\n", " by_cat[c][\"correct\"] += 1\n", "\n", "print(\"Accuracy by category (this is your core finding):\\n\")\n", "for cat, v in by_cat.items():\n", " acc = v[\"correct\"] / v[\"total\"] if v[\"total\"] else 0\n", " print(f\" {cat:<10}: {v['correct']}/{v['total']} = {acc:.0%}\")\n", "\n", "# Save results so you can attach them to the HF repo\n", "with open(\"eval_results.json\", \"w\", encoding=\"utf-8\") as f:\n", " json.dump(results, f, ensure_ascii=False, indent=2)\n", "print(\"\\nSaved eval_results.json\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "collapsed": true, "id": "1O0R57uFksyu", "outputId": "3e00ec4a-1cde-4b1d-c3dc-35dd191bef88" }, "execution_count": 9, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Accuracy by category (this is your core finding):\n", "\n", " known_cve : 2/3 = 67%\n", " mutated : 0/3 = 0%\n", " patched : 3/3 = 100%\n", " fake : 3/3 = 100%\n", "\n", "Saved eval_results.json\n" ] } ] }, { "cell_type": "code", "source": [ "model.push_to_hub(\"Zeineb12/evaluation-artifacts\")\n", "tokenizer.push_to_hub(\"Zeineb12/evaluation-artifacts\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 504, "referenced_widgets": [ "2dc9826dac1842078dae0022f5e5d3c4", "591cae8b89bf47ae9ea2e946ec5bb483", "716b0360a3134574b37b30e31be41d07", "7f1aa63a1f104d0ba616836d51ea6138", "ef431f87cc7a45039235d312ae6322d2", "7a98a5df0e714e72b622661fe0b0169c", "19e1789b3a964c29996ff4a760fae562", "f8c1c04f9996404cb5c687033a8f74d1", "aa123f1e99374dacaf24fc9ee3f2f5b6", "5f77fbf5ffe94ecba5e6bbfc55250d1d", "361e7b9d0eeb41a880c12bb30fae5257", "bec977a777cd44568915144aede2199f", "fa0faa918e2e45aa8d639d020c1f8e25", "da8afd071fab464a8405ce3dc42a0695", "1203987b6bc24920a9516889171746ca", "9403ea2b918e4c7eb05147eb7e2b6861", "62e243eeebc948c198505ebdb0e31748", "41d2180939114428a3caa58728fe8d97", "89fb52e317754036aa4bd255ac3d44d2", "02195d73a263475fb5910f05047388b4", "2964078921c54f89865ac45ca4eaa977", "882f409f6e1f414eb19ba7580c65d364", "dffe42cd6e8e4b18b722d2456bb68622", "42f13f9b6c9b42b1a69ab29a30f8964a", "50e6e215cacd481682d72f6e1b59a1b0", "50e6b0a25a514621b97add3417636731", "1e25a32e9a734a97b5eca45363edddd6", "799a07bb2ab449c4adaacdceb2bd100b", "cfe0ba322d6a4928b524fc3b4140f2d1", "023df7eae06f440e9848d69ed92752f5", "20e91b2fd1384fb0a4ea4f9721c473d3", "115b7100f5554ddbb4730690a3fcd4a3", "ed4ea3eafb7046d695cd33e3cd3f7e9c", "d0ab56603f4d4d389f54692c87470df4", "b292acc27570422c86fbf24156666f13", "c8d15fb746554f27b14aaf3ad582dc4a", "2db0d89fc35d49faa2e0380cfeada29b", "ca664ccd56cd4e07b58557c32a3bd98b", "7a1c1a70983c40afabdf79ec69ffab3d", "8fdf868c6a5a455486853f4cfc20ef1e", "9a7331ceeb7e4649915b9a545e95a870", "8568822975954489a2e2832c3893154c", "13e3738eba4a41d79e9ffe5e2401c261", "92e94fb20be84283a0a0e98344117c95", "72c36e70e92a4d08b3d22ea4b61de663", "9ff5258ee2e7440e8baf19ecf5ecb6d5", "08d28dd366b248a080f1979dc3648fd4", "e01ef6c45f064c3b8f5f80e0c03f10cb", "a04d5f36d5124dba95cbbf59212d7b78", "01c133824f564cf89639a1072d4e3a78", "efe8d305ed33495d9a3538af6195050d", "014d3f2e4734403f97062bad47552b8e", "52ad3946e3e34188873b6f074536420c", "ed72d4c9c4044f359c4ebc2d881d5bb6", "78a65aa66a1b41fcbd7cd038dbf48f8d", "51b91926f3274082b9de5baef55539d8", "5656ad8593af41348efd507669992fce", "4984672b9a2b46788b031ec4e9e8b788", "f9d8f12238654c98881f97fff1a56a75", "0ee9419a0ee347ada98d62fa064d044f", "21bd6086b06d4a21bdbf82e1d28b1693", "6e38952626114ec0b797fd3e8741285e", "1ff06fc927984249b2420b8bf3b31cf1", "60658992677f453895476af2ec57aeb8", "d64bf46fec324ced9cdf28ff9eecbd7e", "ec63a8fa209f49afab7907cbb4cd1570", "84fa5e3dd6494258bae28d7360e385e7", "30c4357cd8b0498cb75643683c539303", "f44281e82ea04c19be7e7d758ea82c91", "5f46eef057134c7594839799fea431f3", "7e26ee4165b843048a5dc364ce3ed9d4", "d7770af46fd843cda6fd1762d6e771ea", "708d78e927c84db8a49875b1118a71af", "0df0c8a8374e40b8a3f0e0b428ba52fa", "62beaae3f1854c5395dbf96e25685245", "0706d1b3d241480e9b7476a64303992b", "b26edf0f7cc347debc55d577784b9cfa", "e70e889d0e88487bb50ffcbaa8a7d6ea", "2d21df3304ab4db6b7ef7b227fc80483", "c775547752fd4a3da2af5bd264569d6f", "64ad077748a6452a8aadd1ecf8dad85b", "acc2e71836224ca784527289801476e7", "6b5d93dc29ab404d84f7384bb4663ed6", "589c229dd71b46f2a547783a1d3e77cd", "e8164c062f5f4070824ee8abe822268d", "b7b1f1f8a0834038a13f184c8e90e26c", "0bafecf682ca4c7ba450ee8e97b6639c", "296faa91ab604f98b73928163be0730e", "842eabc3236a4f588a116e628ddc694b", "2b19c1e2b0a2415284cc617ebe98a79c", "9ce163ff460e48138ec4adb20cc673e2", "08b7218d048044e8be2467b1c02ae6dd", "32126aa019d9494daec4375ac0fc45ba", "8427b254f4c44fde9e8f5cbda1eb3ab1", "82f82efd671b4d2bbe2f747839ceb8f7", "d5e1008c31bf42cfb369ddd7ba534b63", "beae86613ea2489ba7db49fd45b1c035", "5f568186ef9645cbba5d20ea58f41d8a", "02dd2c3844e84599b8024a24950f77f8", "5408fc55cd9f4cbe91001ac3392c7abc", "0ea0b0902ac1419ba7038b820028be8c", "d7c3927345e646f9b87f0c40fdb17058", "79b91bf42a1643e6a4ca0cf1c14d073f", "bdf32f4eb06c414987bc3328826f919e", "07a357b5ac75445bb7182c4273bbdd6a", "39c9dae6f219442b800ba91a28db53fb", "db549f985b3b4d2a9c6770161f122f84", "0483f53704b34539a0f9e60f5a3c4399", "6e2cfbc1c1234c05bbc1056cb6d2852d", "0884b87981e441a0a49a6c9a993669bd" ] }, "collapsed": true, "id": "RhIw94A085bD", "outputId": "dc3ac470-07a5-499a-fb8e-6f65e46d18bc" }, "execution_count": 10, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Writing model shards: 0%| | 0/1 [00:00\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Zeineb12/evaluation-artifacts\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mtokenizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Zeineb12/evaluation-artifacts\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0meval_dataset\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Zeineb12/evaluation-artifacts\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mNameError\u001b[0m: name 'eval_dataset' is not defined" ] } ] }, { "cell_type": "code", "source": [ "import os\n", "os.listdir(\"/content\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1lrTKcZJAsfS", "outputId": "f7dc5b16-da0c-4ec6-cf2e-b8ba0ee64019" }, "execution_count": 11, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "['.config',\n", " 'eval_results.json',\n", " '.ipynb_checkpoints',\n", " 'eval_dataset.jsonl',\n", " 'sample_data']" ] }, "metadata": {}, "execution_count": 11 } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import upload_file\n", "upload_file(\n", " path_or_fileobj=\"/content/eval_dataset.jsonl\",\n", " path_in_repo=\"eval_dataset.jsonl\",\n", " repo_id=\"Zeineb12/evaluation-artifacts\",\n", " repo_type=\"model\",\n", ")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 109 }, "id": "KKJWg8DGAukB", "outputId": "04e82952-47c9-4912-bae9-a169df02e8b5" }, "execution_count": 12, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "CommitInfo(commit_url='https://huggingface.co/Zeineb12/evaluation-artifacts/commit/48c4f631592a5f1a18110439ed051eb68809c509', commit_message='Upload eval_dataset.jsonl with huggingface_hub', commit_description='', oid='48c4f631592a5f1a18110439ed051eb68809c509', pr_url=None, repo_url=RepoUrl('https://huggingface.co/Zeineb12/evaluation-artifacts', endpoint='https://huggingface.co', repo_type='model', repo_id='Zeineb12/evaluation-artifacts'), pr_revision=None, pr_num=None)" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 12 } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import upload_file\n", "upload_file(\n", " path_or_fileobj=\"/content/eval_dataset.jsonl\",\n", " path_in_repo=\"eval_results.json\",\n", " repo_id=\"Zeineb12/evaluation-artifacts\",\n", " repo_type=\"model\",\n", ")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 109 }, "id": "dSG71dZOCoTO", "outputId": "5f3d2589-8d6a-48c4-b899-3c484a03277f" }, "execution_count": 13, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "CommitInfo(commit_url='https://huggingface.co/Zeineb12/evaluation-artifacts/commit/22ef9f2513a86f22bc67705cd2ff9f5726f4c294', commit_message='Upload eval_results.json with huggingface_hub', commit_description='', oid='22ef9f2513a86f22bc67705cd2ff9f5726f4c294', pr_url=None, repo_url=RepoUrl('https://huggingface.co/Zeineb12/evaluation-artifacts', endpoint='https://huggingface.co', repo_type='model', repo_id='Zeineb12/evaluation-artifacts'), pr_revision=None, pr_num=None)" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 13 } ] } ] }