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(1.16.0)\n", "Installing collected packages: pyarrow, dill, multiprocess, datasets\n", " Attempting uninstall: pyarrow\n", " Found existing installation: pyarrow 10.0.1\n", " Uninstalling pyarrow-10.0.1:\n", " Successfully uninstalled pyarrow-10.0.1\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", "ibis-framework 7.1.0 requires pyarrow<15,>=2, but you have pyarrow 15.0.0 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed datasets-2.17.0 dill-0.3.8 multiprocess-0.70.16 pyarrow-15.0.0\n" ] }, { "output_type": "display_data", "data": { "application/vnd.colab-display-data+json": { "pip_warning": { "packages": [ "pyarrow" ] } } }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "import os\n", "import sys\n", "import transformers\n", "import tensorflow as tf\n", "from datasets import load_dataset\n", "from transformers import AutoTokenizer\n", "from transformers import TFAutoModelForSeq2SeqLM, DataCollatorForSeq2Seq\n", "from transformers import AdamWeightDecay\n", "from transformers import AutoTokenizer, TFAutoModelForSeq2SeqLM" ], "metadata": { "id": "fpU13D5UdR_w" }, "execution_count": 1, "outputs": [] }, { "cell_type": "code", "source": [ "model_checkpoint = \"Helsinki-NLP/opus-mt-en-hi\"" ], "metadata": { "id": "-bfBjykHdT49" }, "execution_count": 2, "outputs": [] }, { "cell_type": "code", "source": [ "raw_datasets = load_dataset(\"cfilt/iitb-english-hindi\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 377, "referenced_widgets": [ "fe5b0df948cb40e49a936c54d9621209", "d3938b3ba55d42db982500594f13530c", "ead1b5de586d40098da5598c0af5252c", "0f93b7e200ce4b8aa0d6f7f27091533d", "c0445f5d959e47459e21dbc3c0467f69", "481e9b12387e4f20a17a4d403252d88a", "65e74b0b49184bb4be65535b1a1e0bf8", "00f584d4f32d4a19aac09663de4bec99", "85b23d67682b4205856b3623ca6e123c", "e06f69261b4f450fb0ed63b69cd38e41", "02c048992aeb407bacbd0875b66e253e", "994ec461ad6546c5bb33b4da21815ea9", "22c26e7e140946a7be1b8aa316df57ec", "4646ce0ee7bb4b5191595552d34f41dc", "4e4f7fcbf9934a968700483055a51785", "6dbbc5ca3c3c418699edcdbc52104b2e", "83f3553b36db4ddfb6634a5c1a861609", "9851a2a4d4084f6297c99eacb2c84a51", "3335b388879147abbbed4cc1ff748a3e", "15c6a35213c44e1d8ebba1cced6e4212", "fcba666d7bfe446686c0a160ea5571ae", "90af88622b614b3aa7a3870c59bafff8", "6409614929aa43d4b2ea934e91281a02", "41072b10bf32413d9cda79e6adcdf38c", "a4201f8cc87141588f7b47cb55a83d19", "00b2ad58e80d482cb422e59e868a3a2a", "aa70385e30244728ba2beeaaa798dc81", "96a963cb744841a3936692b1fa452e4c", "a2f1f5d5e9684767aadb7bb775c9d37c", "399200d01d6046d0bb04b93c813722d6", "4bb90177b03846e7a43fdef8c96dc8e5", "df4220324e294776b24dae0dc7493705", "2c373956603e405894765fbd909ef6f2", "9fa426d65a154377b31682b513383b69", "dc0c049d759b482bb5cdd66d3672cf48", "2e3b001a86904b7da5331da246537a2e", "8b2ff742e8404f90a0bc6362d2aa111a", "b7075135807f489ea6f973ec2c2d3b1f", "162be5ba52194b47ac3d564a52fcdf96", "cc3b0090713445c196cdec80250f828f", "2ba3ba88c0ac499da2ee508b37177c1f", "53cb6c0ebbe54c1182a2f58d746f7053", "23f55d4b1690439a8051c6dd9026c69a", "c443c35ff9bf4567928b6ea89f432f2e", "85551d737d4b419197ee409f6d79d143", "b3299ea8716b415b99bd4cd46a3597a3", "bff9f7eae6a049e3b5301a3db6cd30fd", "2841af335ad343c7a754a2c85487ace7", "4e4a6b4b30e4403ca987d87f5ccf7a12", "8adae8bfdfc04decb9c4144bfbc32568", "a4f9532345054e7dbf49e1a31634d915", "ea8cad802bff4137b01815b7254e8fff", "be157ac9132a4128a1feb9adae63a51a", "3197703ec5fa4baf8303189dee29d5d5", "fd888752e9d7451da3717c7b42c6f19c", "fed95ec9257b4f30894877940bf09671", "59677ae122e44c67952821fe14b88d63", "5f6394768a8a4608840791613620ee22", "ef1272a7c9964e40a1e8d1872e21fe0d", "4c39a9544f384416ae1244d1f2f01980", "c3f50c17427b4d53b01bb39a32ae474e", "35f148a3382b4b078928d825cf21da9b", "585be5fda1ad49de897552252b84f6b8", "fea2c5ec4a1e48afa090bcdfa399cf76", "eb5da93b907849198e4e35fcbf4a90f2", "877d99b663f94b61987a9271e7e5ba26", "652cfa71abb44206bf0f9aaf088fd522", "831dcdf5b4a24f91b0e9fbed9bfd230d", "ccc08e967547485da91c6462dffb5dd2", "1eaf997e6b9b437a81bf85ff2af0ee6a", "72c67c22dfbb47149b7c8660d017584b", "085d7c3baa064a77bde33c2883c2036f", "17ff9028322243258757ca5091b40fa2", "520c83afadf44e5d99b37750e839d9c1", "5a9d4bc19eff4e5780527577206b83f7", "b7dca9de71b74f28924233bb6b10ec9f", "a884e9bb30d4468d95183aa84be2aaf8", "41abb8846f434015b0b03ec5f6ffdbd9", "2971d3dd7b604da288599b933e0a0cd3", "da1eb2b57bf54da5b45d75de7c16a7d4", "da978449bf0d46bea760a11410238b1c", "3c85246488e543f8af1e2bec6d89aee2", "c0d5e14979904927928baceb234b0e9e", "7722ffdafd8e4db498127ce626c380a3", "ae06e96dfb964a9eadb4a988a095a095", "d551ab2346584718a430f5dd7f8653a5", "be57b26ec2754b1299d7d692f3517b6d", "e289c3255c714981b7216744418a5b04" ] }, "id": "NbzDGrOndT7i", "outputId": "258a8077-4234-4376-e746-384565c28429" }, "execution_count": 3, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n", "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", "You will be able to reuse this secret in all of your notebooks.\n", "Please note that authentication is recommended but still optional to access public models or datasets.\n", " warnings.warn(\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading readme: 0%| | 0.00/3.14k [00:00" ] }, "metadata": {}, "execution_count": 17 } ] }, { "cell_type": "code", "source": [ "model.save_pretrained(\"tf_model/\")" ], "metadata": { "id": "K0pxKc9_d9Ct" }, "execution_count": 18, "outputs": [] }, { "cell_type": "code", "source": [ "tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)\n", "model = TFAutoModelForSeq2SeqLM.from_pretrained(\"tf_model/\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "d5E8zVuVd9E_", "outputId": "e1725ec0-8467-4908-812b-cca2da087b13" }, "execution_count": 19, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/transformers/models/marian/tokenization_marian.py:197: UserWarning: Recommended: pip install sacremoses.\n", " warnings.warn(\"Recommended: pip install sacremoses.\")\n", "All model checkpoint layers were used when initializing TFMarianMTModel.\n", "\n", "All the layers of TFMarianMTModel were initialized from the model checkpoint at C:/Users/Vishwas/Desktop/personal/major project/firdous/tf_model/.\n", "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFMarianMTModel for predictions without further training.\n" ] } ] }, { "cell_type": "code", "source": [ "input_text = \"My name vishwas i am student\"\n", "\n", "tokenized = tokenizer([input_text], return_tensors='np')\n", "out = model.generate(**tokenized, max_length=128)\n", "with tokenizer.as_target_tokenizer():\n", " print(tokenizer.decode(out[0], skip_special_tokens=True))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Tgfh0Gh_d9F3", "outputId": "b35d2021-e5cb-4101-a8f5-7ae02a4cd330" }, "execution_count": 21, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "मेरा नाम वेशय था- कि मैं विद्यार्थी हूँ\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:3856: UserWarning: `as_target_tokenizer` is deprecated and will be removed in v5 of Transformers. You can tokenize your labels by using the argument `text_target` of the regular `__call__` method (either in the same call as your input texts if you use the same keyword arguments, or in a separate call.\n", " warnings.warn(\n" ] } ] }, { "cell_type": "code", "source": [ "from transformers import TFAutoModelForSeq2SeqLM\n", "\n", "model_path = \"C:/Users/Vishwas/Desktop/personal/major project/firdous/tf_model/\"\n", "model = TFAutoModelForSeq2SeqLM.from_pretrained(model_path)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Ox4IkwAYd9Lc", "outputId": "6824b6d8-1b27-4028-e287-6515b0932a67" }, "execution_count": 22, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "All model checkpoint layers were used when initializing TFMarianMTModel.\n", "\n", "All the layers of TFMarianMTModel were initialized from the model checkpoint at C:/Users/Vishwas/Desktop/personal/major project/firdous/tf_model/.\n", "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFMarianMTModel for predictions without further training.\n" ] } ] }, { "cell_type": "code", "source": [ "input_text = \"My name vishwas i am student\"\n", "\n", "tokenized = tokenizer([input_text], return_tensors='np')\n", "out = model.generate(**tokenized, max_length=128)\n", "with tokenizer.as_target_tokenizer():\n", " print(tokenizer.decode(out[0], skip_special_tokens=True))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "b9vHs7QElGId", "outputId": "5ac5854a-623d-4432-cf1c-b0b08b8ac14b" }, "execution_count": 26, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "मेरा नाम वेशय था- कि मैं विद्यार्थी हूँ\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:3856: UserWarning: `as_target_tokenizer` is deprecated and will be removed in v5 of Transformers. You can tokenize your labels by using the argument `text_target` of the regular `__call__` method (either in the same call as your input texts if you use the same keyword arguments, or in a separate call.\n", " warnings.warn(\n" ] } ] }, { "cell_type": "code", "source": [], "metadata": { "id": "bz-W-tSdmT0-" }, "execution_count": null, "outputs": [] } ] }