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eval-gsm8k-microsoft-phi-2-colab.ipynb
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"\n",
"GSM-8k colab\n",
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],
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"Cloning into 'lm-evaluation-harness'...\n",
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"Receiving objects: 100% (2631/2631), 1.04 MiB | 20.13 MiB/s, done.\n",
"Resolving deltas: 100% (1035/1035), done.\n",
"/content/lm-evaluation-harness\n",
"Obtaining file:///content/lm-evaluation-harness\n",
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
" Checking if build backend supports build_editable ... \u001b[?25l\u001b[?25hdone\n",
" Getting requirements to build editable ... \u001b[?25l\u001b[?25hdone\n",
" Preparing editable metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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"Installing collected packages: sqlitedict, zstandard, tcolorpy, pybind11, portalocker, pathvalidate, mbstrdecoder, jsonlines, dill, colorama, typepy, tqdm-multiprocess, sacrebleu, rouge-score, responses, multiprocess, accelerate, datasets, DataProperty, tabledata, peft, evaluate, pytablewriter, lm_eval\n",
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]
}
]
},
{
"cell_type": "code",
"source": [
"%pip install transformers~=4.37.0"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 548
},
"id": "FlUYnC7vKb2u",
"outputId": "ca74d123-7ea3-4c6b-a208-0abd4e1875ea"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting transformers~=4.37.0\n",
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"Installing collected packages: transformers\n",
" Attempting uninstall: transformers\n",
" Found existing installation: transformers 4.35.2\n",
" Uninstalling transformers-4.35.2:\n",
" Successfully uninstalled transformers-4.35.2\n",
"Successfully installed transformers-4.37.1\n"
]
},
{
"output_type": "display_data",
"data": {
"application/vnd.colab-display-data+json": {
"pip_warning": {
"packages": [
"transformers"
]
}
}
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"import torch\n",
"from transformers import AutoModelForCausalLM, AutoTokenizer\n",
"\n",
"torch.set_default_device(\"cuda\")\n",
"\n",
"model = AutoModelForCausalLM.from_pretrained(\"microsoft/phi-2\", torch_dtype=\"auto\", trust_remote_code=True)\n",
"tokenizer = AutoTokenizer.from_pretrained(\"microsoft/phi-2\", trust_remote_code=True)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 922,
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},
"id": "KgDdu2-DKLct",
"outputId": "26521b24-1a98-4353-e29e-5378ed81d777"
},
"execution_count": null,
"outputs": [
{
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}
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"def print_prime(n):\n",
" \"\"\"\n",
" Print all primes between 1 and n\n",
" \"\"\"\n",
" for i in range(2, n+1):\n",
" for j in range(2, i):\n",
" if i % j == 0:\n",
" break\n",
" else:\n",
" print(i)\n",
"\n",
"print_prime(20)\n",
"```\n",
"\n",
"## Exercises\n",
"\n",
"1. Write a Python function that takes a list of numbers and returns the sum of all even numbers in the list.\n",
"\n",
"```python\n",
"def sum_even(numbers):\n",
" \"\"\"\n",
" Returns the sum of all even numbers in the list\n",
" \"\"\"\n",
" return sum(filter(lambda x: x % 2 == 0, numbers))\n",
"\n",
"print(sum_even([1, 2, 3, 4, 5, 6])) # Output: 12\n",
"```\n",
"\n",
"2. Write a Python function that takes\n"
]
}
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "qozAmVRGJPsw",
"outputId": "4508a40c-9395-4b87-fb7c-82d34752d892"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2024-01-26:23:48:06,395 INFO [utils.py:148] Note: NumExpr detected 12 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n",
"2024-01-26:23:48:06,395 INFO [utils.py:160] NumExpr defaulting to 8 threads.\n",
"2024-01-26:23:48:06,654 INFO [config.py:58] PyTorch version 2.1.0+cu121 available.\n",
"2024-01-26:23:48:06,655 INFO [config.py:95] TensorFlow version 2.15.0 available.\n",
"2024-01-26:23:48:06,656 INFO [config.py:108] JAX version 0.4.23 available.\n",
"2024-01-26 23:48:07.142969: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
"2024-01-26 23:48:07.143030: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
"2024-01-26 23:48:07.144746: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
"2024-01-26 23:48:08.258559: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
"2024-01-26:23:48:12,109 INFO [__main__.py:156] Verbosity set to INFO\n",
"2024-01-26:23:48:16,514 WARNING [__init__.py:194] Some tasks could not be loaded due to missing dependencies. Run with `--verbosity DEBUG` for full details.\n",
"2024-01-26:23:48:20,715 WARNING [__init__.py:194] Some tasks could not be loaded due to missing dependencies. Run with `--verbosity DEBUG` for full details.\n",
"2024-01-26:23:48:20,716 INFO [__main__.py:229] Selected Tasks: ['gsm8k']\n",
"2024-01-26:23:48:20,726 INFO [huggingface.py:148] Using device 'cuda:0'\n",
"Loading checkpoint shards: 100% 2/2 [00:02<00:00, 1.37s/it]\n",
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
"Downloading readme: 100% 7.94k/7.94k [00:00<00:00, 29.0MB/s]\n",
"Downloading data: 100% 2.31M/2.31M [00:00<00:00, 6.44MB/s]\n",
"Downloading data: 100% 419k/419k [00:00<00:00, 1.55MB/s]\n",
"Generating train split: 100% 7473/7473 [00:00<00:00, 169280.80 examples/s]\n",
"Generating test split: 100% 1319/1319 [00:00<00:00, 413474.36 examples/s]\n",
"2024-01-26:23:48:32,058 INFO [task.py:340] Building contexts for task on rank 0...\n",
"2024-01-26:23:48:40,717 INFO [evaluator.py:319] Running generate_until requests\n",
"100% 1319/1319 [18:31<00:00, 1.19it/s]\n",
"fatal: not a git repository (or any of the parent directories): .git\n",
"hf (pretrained=microsoft/phi-2), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 8\n",
"|Tasks|Version| Filter |n-shot| Metric |Value | |Stderr|\n",
"|-----|------:|----------|-----:|-----------|-----:|---|-----:|\n",
"|gsm8k| 2|get-answer| 5|exact_match|0.5785|± |0.0136|\n",
"\n"
]
}
],
"source": [
"!lm_eval --model hf \\\n",
" --model_args pretrained=microsoft/phi-2 \\\n",
" --tasks gsm8k \\\n",
" --device cuda:0 \\\n",
" --batch_size 16"
]
},
{
"cell_type": "code",
"source": [
"!lm_eval --model hf \\\n",
" --model_args pretrained=microsoft/phi-1_5 \\\n",
" --tasks gsm8k \\\n",
" --device cuda:0 \\\n",
" --batch_size 16"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "5InDsOXgJw3W",
"outputId": "4ee62712-5985-40d1-eba2-21fb6c3d06eb"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2024-01-27:00:10:14,629 INFO [utils.py:148] Note: NumExpr detected 12 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n",
"2024-01-27:00:10:14,629 INFO [utils.py:160] NumExpr defaulting to 8 threads.\n",
"2024-01-27:00:10:14,892 INFO [config.py:58] PyTorch version 2.1.0+cu121 available.\n",
"2024-01-27:00:10:14,892 INFO [config.py:95] TensorFlow version 2.15.0 available.\n",
"2024-01-27:00:10:14,893 INFO [config.py:108] JAX version 0.4.23 available.\n",
"2024-01-27 00:10:15.383830: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
"2024-01-27 00:10:15.383920: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
"2024-01-27 00:10:15.385733: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
"2024-01-27 00:10:16.474088: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
"2024-01-27:00:10:20,284 INFO [__main__.py:156] Verbosity set to INFO\n",
"2024-01-27:00:10:24,710 WARNING [__init__.py:194] Some tasks could not be loaded due to missing dependencies. Run with `--verbosity DEBUG` for full details.\n",
"2024-01-27:00:10:28,875 WARNING [__init__.py:194] Some tasks could not be loaded due to missing dependencies. Run with `--verbosity DEBUG` for full details.\n",
"2024-01-27:00:10:28,876 INFO [__main__.py:229] Selected Tasks: ['gsm8k']\n",
"2024-01-27:00:10:28,886 INFO [huggingface.py:148] Using device 'cuda:0'\n",
"config.json: 100% 864/864 [00:00<00:00, 4.64MB/s]\n",
"pytorch_model.bin: 100% 2.84G/2.84G [00:09<00:00, 303MB/s]\n",
"/usr/local/lib/python3.10/dist-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n",
" return self.fget.__get__(instance, owner)()\n",
"generation_config.json: 100% 74.0/74.0 [00:00<00:00, 473kB/s]\n",
"tokenizer_config.json: 100% 237/237 [00:00<00:00, 1.33MB/s]\n",
"vocab.json: 100% 798k/798k [00:00<00:00, 3.25MB/s]\n",
"merges.txt: 100% 456k/456k [00:00<00:00, 1.92MB/s]\n",
"tokenizer.json: 100% 2.11M/2.11M [00:00<00:00, 64.2MB/s]\n",
"added_tokens.json: 100% 1.08k/1.08k [00:00<00:00, 6.35MB/s]\n",
"special_tokens_map.json: 100% 99.0/99.0 [00:00<00:00, 591kB/s]\n",
"2024-01-27:00:10:49,314 INFO [task.py:340] Building contexts for task on rank 0...\n",
"2024-01-27:00:10:57,972 INFO [evaluator.py:319] Running generate_until requests\n",
"100% 1319/1319 [09:06<00:00, 2.41it/s]\n",
"fatal: not a git repository (or any of the parent directories): .git\n",
"hf (pretrained=microsoft/phi-1_5), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 16\n",
"|Tasks|Version| Filter |n-shot| Metric |Value | |Stderr|\n",
"|-----|------:|----------|-----:|-----------|-----:|---|-----:|\n",
"|gsm8k| 2|get-answer| 5|exact_match|0.3192|± |0.0128|\n",
"\n"
]
}
]
}
]
}
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