diff --git "a/HuggingFaceH4_zephyr-7b-alpha.ipynb" "b/HuggingFaceH4_zephyr-7b-alpha.ipynb"
--- "a/HuggingFaceH4_zephyr-7b-alpha.ipynb"
+++ "b/HuggingFaceH4_zephyr-7b-alpha.ipynb"
@@ -1 +1 @@
-{"cells":[{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":56281,"status":"ok","timestamp":1699017193765,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"ne6y4KvsP-YK","outputId":"030da997-b35b-4656-ca61-c991c5bd1666"},"outputs":[{"name":"stdout","output_type":"stream","text":["Collecting git+https://github.com/huggingface/transformers@main\n","  Cloning https://github.com/huggingface/transformers (to revision main) to c:\\users\\lruiz\\appdata\\local\\temp\\pip-req-build-hj4kym99\n","  Resolved https://github.com/huggingface/transformers to commit e9dbd3926317a4effb1d033d8454ff18280d0b7d\n","  Installing build dependencies: started\n","  Installing build dependencies: finished with status 'done'\n","  Getting requirements to build wheel: started\n","  Getting requirements to build wheel: finished with status 'done'\n","  Preparing metadata (pyproject.toml): 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kB)\n","Installing collected packages: libclang, flatbuffers, wrapt, werkzeug, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, pyasn1, protobuf, opt-einsum, oauthlib, ml-dtypes, markdown, keras, h5py, grpcio, google-pasta, gast, cachetools, astunparse, absl-py, rsa, requests-oauthlib, pyasn1-modules, google-auth, google-auth-oauthlib, tensorboard, tensorflow-intel, tensorflow\n","Successfully installed absl-py-2.0.0 astunparse-1.6.3 cachetools-5.3.2 flatbuffers-23.5.26 gast-0.5.4 google-auth-2.23.4 google-auth-oauthlib-1.0.0 google-pasta-0.2.0 grpcio-1.59.2 h5py-3.10.0 keras-2.14.0 libclang-16.0.6 markdown-3.5.1 ml-dtypes-0.2.0 oauthlib-3.2.2 opt-einsum-3.3.0 protobuf-4.25.0 pyasn1-0.5.0 pyasn1-modules-0.3.0 requests-oauthlib-1.3.1 rsa-4.9 tensorboard-2.14.1 tensorboard-data-server-0.7.2 tensorflow-2.14.0 tensorflow-estimator-2.14.0 tensorflow-intel-2.14.0 tensorflow-io-gcs-filesystem-0.31.0 termcolor-2.3.0 werkzeug-3.0.1 wrapt-1.14.1\n","Note: you may need to restart the kernel to use updated packages.\n"]},{"name":"stderr","output_type":"stream","text":["  Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers 'C:\\Users\\lruiz\\AppData\\Local\\Temp\\pip-req-build-hj4kym99'\n"]}],"source":["%pip install accelerate gradio torch torchvision tensorflow diffusers git+https://github.com/huggingface/transformers@main"]},{"cell_type":"code","execution_count":6,"metadata":{"executionInfo":{"elapsed":15548,"status":"ok","timestamp":1699017209308,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"BACO2_fs0Db-"},"outputs":[],"source":["from transformers import AutoTokenizer, AutoModelForSeq2SeqLM\n","import torch\n","from transformers import pipeline\n","import tensorflow as tf"]},{"cell_type":"code","execution_count":9,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":938,"referenced_widgets":["7d1e457e201440d88b4a1a9daeb38caf","3d85861278aa46e7b89b76591794ff2a","e2d975fb90d84c39a2f98c0403d58a4f","c66953da4e684f86b89f236b32276d73","e669535f0ea345cd92119a8d5752437e","3a0f4dfe79ff4140aa22dea3a9223a3f","e9d94c0425bc48948ef1ab32fff4a67d","834f8b7d1a1f4c67911eac48539e5e75","799ea3f9508640b6b02b0ade6ebd0472","f2a16fe3a30642b2a67b5e70224246e4","ad35d7b8073d43d8a16a26dbb7515af6","1e594c0b7feb4678ac7b840795c8e7f1","f14680f9294a47c7b416b651535e46b7","bb3c142669eb485081ff2e00020825ec","45c5a465024d4ce3949c1cf3b622fc84","6e898e6f80c94b3499a645dfee5d9053","2f9157aabde8495eaf6bb87a6e109424","f4bf5d13e5a843f4a7caf83a0e262921","f4d16b9fed0d40f38f3513da0321ee00","c9e39f3c8dd54c1cad4db1358b7122c9","944a5d7ae32a45508d79262127093488","a8dd0a8d66cf4f00b5f112c5c0a55a9d","c3ad38bc4b124a56a6c06a831f890ed1","731832bfa3ba4311aed3fcceb040fa99","207c8d19421b42f693ca7d37f8bfb897","39d807e94cc64360abe905df12722605","bf25a6a0257748aeb06c3a05899eaaeb","4b3a0648ad114a7f9f3403285a736db5","7047d198053c4cde9d4b1093e5d92a10","58efa5a151c5466fb84cebed7dbfd42c","73387218e252445f9f46e76f1f119394","c902eca15a1d4756a613cc55d2dd9cb3","fe63aa6d1c2b496eb59c48d2304de08b","447c6b8169c44d96b2d8503da205279b","43e320eb30ef46ddb11502eb8e872404","8c9cd843ab274c2e86247888a50d1ae0","a0b21d301a7f4c19802a59a2766ab5f8","55fc7dfc7c8a4674b46bd5acd377d326","f0632473f0ad4526ac10b4d84fb9ed05","86068044f76a4b94bfcbefde2eea07a9","af5ddff71c7a4384afd70e80ef9e8418","ad74a672cbc34d9eb1622cd4885649a5","edc38d226a1d48b9ab1a9d04fe5e8b3a","5a4faa1ba8e2423a9e20aefdcefe02c5","f3659a28119149cb860747cf6ca96e93","81446aef1bcb469aaeaab06d2a7a1836","e92b7cb8c79e4367bcc2a77fff7f77a7","5c898338a94f4490a6ba282c51945d9f","974d9fdd0def429da0b87b05462a06a7","52dc5d29c1e24ef4b51ea88e5a201986","8b09b3dffa4e4178947b5250b5cb650b","8d8eec4707904c709099cfd7218d0d45","4f927b9e3eb34de38856c870e3b038c5","5f811ae4d60b4d90b6749fe6d082c266","e937f6191ed442359f0d3ba6fcf3bb95","b99d1c8439224253992053725bf14998","95d71ae64f7247908fe6672e3d479586","c08ee03a824a440583134a341240b0f4","f4349e2c0e1240db8d5a4d119ac5d132","4fa4467b02ce428cbcca47f5793f03d5","4210922217484924af1d89e7f50d4484","9b6d50eb5f03457d8f1bbf9d377a14ae","d4081643d2ce4eb68c4f58169f6e8076","49bb40085f1f432f835c8ba9815092b0","87be10185dcc4d9c8435310544930ca9","b7cd789702234c768e12951040d1b8b9","f7a22c8221c84190a02a215d6e1f16b2","b7197909f90c4d00aeb6781d91147718","5154123d93de4c399eb8cfbdb700b90c","3163bff0987e4bbe8da8bee82feb47cd","d82d0810d8bd4f30af3d6a13fd55a3c0","a89d30a3716044bc80847a0333405380","daff27c599274b019f1ed1e5e7c8de89","a9c91064d9c8442391cc6fe3b6f7f86e","d1f29df1e9af4798bcfbdf74547413fb","bd2ed5bbfe5f43bdbe00d5d2371c3242","72cd761f610f46238676c780d5e5f4ce","8cbb637a3ad44a329cd87521a205abcd","6aedf8a3ede749ee8e5b9c6289f13f8f","0ff7509ee3a24892aad461ae46af68fa","e28eb5d928864fd087776d09f8387072","adcf3bd1316f40e5ae6c62b7cf62fb11","44be767986ce42329e7d94182aed5d61","f4292a7978434c339802bb1ac150ab58","99ff263aef2046a393e5059cde0252f0","f2e2ff3e060d4e5bbc97eb1ffdcaebd7","f936c133ac1a4953bef167d3f5f7e218","49795449c3254e8393ea83ca8d82ef0c","ffeb044090fd499f81fed5bb14db3d2c","be498966618f4df3b05e3ea0b78639a2","4eb1bc6258aa4f7f840c02a891a5cf68","1426187bf9f047eea13f037b8e30e009","a3aee1891d664044a441c7072e5e7138","1e8551f39f304e308ce6a498405f3df2","1116a53a58db40ee95230e9b88a4a7ca","744a955eb95b4b4399969409c4467466","62ad1e5b11e341179e60e19d5cbf2ba2","043161d8675c46049b3cc1cb719fa210","774661a1755142d1a663173b70233228","70a9d601f9ec424180da879726b638f0","36c3ddb362dc4176985f6c942101daef","d42d9692f71c4768b243d354b0ab816e","d72b1c356a534f0995b071dc9e20e861","cfd7fa1f38a44aaaaf08662b6f9d8831","2193a45797df4a3f9b84a505a0ed96df","bdfdef0327fe485a9868493c59385b65","66909d7d62e940959c2710e946c14104","2f1dc795b73245de84e2cee08b95050e","a15fa142ef904c1f8521115fcffbe704","a218c2949baa4e2d91f5a12318c34f78","0170ea53ea47441e846c7469c1e4f23a","c84203a627284774ab51a47860aa61e0","fa4d8d0270dc41b584409f182c34818e","0dcb667c46cd404aaac4ed26b770b635","ca97c092a79d46cd9d23da559a683df8","f6d557c77492410dbd477014b516ac2c","6bc00e3dd1924dd284bff0cdeb48599d","6019ef2a5d0f408c86b3511283d03f35","5a043889aa70429885689ff6fc9fea51","55326275e7764853b5b3f9d5cfa32706","f6b426495f3d462eae9a269bd64631d9","b98beae45a794c0f86717835185e92b3","4f81e1abbf7041c4a2bc68ef3f5f6c2d","38ee79b79d5b492898d941de66ada836","36929b3c13f64f929b0d1776e0d2db0c","bb00c69316f54322a6b26d07233e0bcc","ea163eadf7994fc684ab35d6d210e23b","6316c2751041485db5765f3a22aedd25","c3e1b074dc52452080ad1e44a10471c0","841ab57427494745ac70476aa30eaf50","62db67408a9049fb8207589d2a137587","1b85c8cf830c430a9bfc8bbcf4918670","76cdccccab0c4706929272e12bcb859d","97d7b6b051c949cf8d5ae3b3a68d0228","31e7d1d38995426e94351225b6e7ecab","924dd0fe501e48aab87824807f081296","9640e1dc14564482961781017d90a5f2","bb4d86de68984808bfd4a4e0b42a3082","75cf764dabfc4a9ca9869318164e49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Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"BHEVUef40Ke8","outputId":"6d967e8d-ebb2-4471-f478-30920898d547"},"outputs":[{"ename":"OSError","evalue":"Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum does not appear to have a file named pytorch_model.bin but there is a file for TensorFlow weights. Use `from_tf=True` to load this model from those weights.","output_type":"error","traceback":["\u001b[1;31m---------------------------------------------------------------------------\u001b[0m","\u001b[1;31mOSError\u001b[0m                                   Traceback (most recent call last)","\u001b[1;32mc:\\Users\\lruiz\\Desktop\\GitHub\\PerfectGPT\\HuggingFaceH4_zephyr-7b-alpha.ipynb Celda 3\u001b[0m line \u001b[0;36m3\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/lruiz/Desktop/GitHub/PerfectGPT/HuggingFaceH4_zephyr-7b-alpha.ipynb#W2sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39m# chatgpt-gpt4-prompts-bart-large-cnn-samsum\u001b[39;00m\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/lruiz/Desktop/GitHub/PerfectGPT/HuggingFaceH4_zephyr-7b-alpha.ipynb#W2sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m tokenizer \u001b[39m=\u001b[39m AutoTokenizer\u001b[39m.\u001b[39mfrom_pretrained(\u001b[39m\"\u001b[39m\u001b[39mKaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/lruiz/Desktop/GitHub/PerfectGPT/HuggingFaceH4_zephyr-7b-alpha.ipynb#W2sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m model \u001b[39m=\u001b[39m AutoModelForSeq2SeqLM\u001b[39m.\u001b[39;49mfrom_pretrained(\u001b[39m\"\u001b[39;49m\u001b[39mKaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/lruiz/Desktop/GitHub/PerfectGPT/HuggingFaceH4_zephyr-7b-alpha.ipynb#W2sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m \u001b[39m# zephyr\u001b[39;00m\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/lruiz/Desktop/GitHub/PerfectGPT/HuggingFaceH4_zephyr-7b-alpha.ipynb#W2sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m pipe \u001b[39m=\u001b[39m pipeline(\u001b[39m\"\u001b[39m\u001b[39mtext-generation\u001b[39m\u001b[39m\"\u001b[39m, model\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mHuggingFaceH4/zephyr-7b-alpha\u001b[39m\u001b[39m\"\u001b[39m, torch_dtype\u001b[39m=\u001b[39mtorch\u001b[39m.\u001b[39mbfloat16, device_map\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mauto\u001b[39m\u001b[39m\"\u001b[39m)\n","File \u001b[1;32mc:\\Users\\lruiz\\miniforge3\\envs\\py311\\Lib\\site-packages\\transformers\\models\\auto\\auto_factory.py:566\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[1;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[0;32m    564\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39mtype\u001b[39m(config) \u001b[39min\u001b[39;00m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39m_model_mapping\u001b[39m.\u001b[39mkeys():\n\u001b[0;32m    565\u001b[0m     model_class \u001b[39m=\u001b[39m _get_model_class(config, \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39m_model_mapping)\n\u001b[1;32m--> 566\u001b[0m     \u001b[39mreturn\u001b[39;00m model_class\u001b[39m.\u001b[39;49mfrom_pretrained(\n\u001b[0;32m    567\u001b[0m         pretrained_model_name_or_path, \u001b[39m*\u001b[39;49mmodel_args, config\u001b[39m=\u001b[39;49mconfig, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mhub_kwargs, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs\n\u001b[0;32m    568\u001b[0m     )\n\u001b[0;32m    569\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[0;32m    570\u001b[0m     \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mUnrecognized configuration class \u001b[39m\u001b[39m{\u001b[39;00mconfig\u001b[39m.\u001b[39m\u001b[39m__class__\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m for this kind of AutoModel: \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mcls\u001b[39m\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m.\u001b[39m\u001b[39m\\n\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[0;32m    571\u001b[0m     \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mModel type should be one of \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m, \u001b[39m\u001b[39m'\u001b[39m\u001b[39m.\u001b[39mjoin(c\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m\u001b[39m \u001b[39m\u001b[39mfor\u001b[39;00m\u001b[39m \u001b[39mc\u001b[39m \u001b[39m\u001b[39min\u001b[39;00m\u001b[39m \u001b[39m\u001b[39mcls\u001b[39m\u001b[39m.\u001b[39m_model_mapping\u001b[39m.\u001b[39mkeys())\u001b[39m}\u001b[39;00m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m    572\u001b[0m )\n","File \u001b[1;32mc:\\Users\\lruiz\\miniforge3\\envs\\py311\\Lib\\site-packages\\transformers\\modeling_utils.py:3078\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[1;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, *model_args, **kwargs)\u001b[0m\n\u001b[0;32m   3072\u001b[0m has_file_kwargs \u001b[39m=\u001b[39m {\n\u001b[0;32m   3073\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39mrevision\u001b[39m\u001b[39m\"\u001b[39m: revision,\n\u001b[0;32m   3074\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39mproxies\u001b[39m\u001b[39m\"\u001b[39m: proxies,\n\u001b[0;32m   3075\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39mtoken\u001b[39m\u001b[39m\"\u001b[39m: token,\n\u001b[0;32m   3076\u001b[0m }\n\u001b[0;32m   3077\u001b[0m \u001b[39mif\u001b[39;00m has_file(pretrained_model_name_or_path, TF2_WEIGHTS_NAME, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mhas_file_kwargs):\n\u001b[1;32m-> 3078\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mEnvironmentError\u001b[39;00m(\n\u001b[0;32m   3079\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mpretrained_model_name_or_path\u001b[39m}\u001b[39;00m\u001b[39m does not appear to have a file named\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   3080\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m \u001b[39m\u001b[39m{\u001b[39;00m_add_variant(WEIGHTS_NAME,\u001b[39m \u001b[39mvariant)\u001b[39m}\u001b[39;00m\u001b[39m but there is a file for TensorFlow weights.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   3081\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39m Use `from_tf=True` to load this model from those weights.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   3082\u001b[0m     )\n\u001b[0;32m   3083\u001b[0m \u001b[39melif\u001b[39;00m has_file(pretrained_model_name_or_path, FLAX_WEIGHTS_NAME, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mhas_file_kwargs):\n\u001b[0;32m   3084\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mEnvironmentError\u001b[39;00m(\n\u001b[0;32m   3085\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00mpretrained_model_name_or_path\u001b[39m}\u001b[39;00m\u001b[39m does not appear to have a file named\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   3086\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m \u001b[39m\u001b[39m{\u001b[39;00m_add_variant(WEIGHTS_NAME,\u001b[39m \u001b[39mvariant)\u001b[39m}\u001b[39;00m\u001b[39m but there is a file for Flax weights. Use\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   3087\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39m `from_flax=True` to load this model from those weights.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m   3088\u001b[0m     )\n","\u001b[1;31mOSError\u001b[0m: Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum does not appear to have a file named pytorch_model.bin but there is a file for TensorFlow weights. Use `from_tf=True` to load this model from those weights."]}],"source":["# chatgpt-gpt4-prompts-bart-large-cnn-samsum\n","tokenizer = AutoTokenizer.from_pretrained(\"Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum\")\n","model = AutoModelForSeq2SeqLM.from_pretrained(\"Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum\", from_tf=True)\n","\n","# zephyr\n","pipe = pipeline(\"text-generation\", model=\"HuggingFaceH4/zephyr-7b-alpha\", torch_dtype=torch.bfloat16, device_map=\"auto\")\n","\n","def useZephyr(prompt):\n","    messages = [\n","        {\n","            \"role\": \"system\",\n","            \"content\": \"You are a friendly chatbot who always responds in the style of a pirate.\",\n","        },\n","        {\"role\": \"user\", \"content\": prompt},\n","    ]\n","    # https://huggingface.co/docs/transformers/main/en/chat_templating\n","    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n","    \n","    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)\n","    return outputs[0][\"generated_text\"]"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":4,"status":"ok","timestamp":1699017517990,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"pL1isZHpY6DF"},"outputs":[],"source":["def generatePrompt(prompt, max_new_tokens):\n","    batch = tokenizer(prompt, return_tensors=\"pt\")\n","    generated_ids = model.generate(batch[\"input_ids\"], max_new_tokens=int(max_new_tokens))\n","    output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)\n","    prompt = output[0]\n","\n","    return useZephyr(prompt)\n","\n","def generate_test(prompt):\n","    batch = tokenizer(prompt, return_tensors=\"pt\")\n","    generated_ids = model.generate(batch[\"input_ids\"], max_new_tokens=150)\n","    output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)\n","    return output[0]\n","\n","def generate_prompt(prompt, max_new_tokens):\n","      return generatePrompt(prompt, max_new_tokens)\n","#"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":646},"executionInfo":{"elapsed":7653,"status":"ok","timestamp":1699017525641,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"U9q8eO_faoVX","outputId":"67b4e6dc-6b5d-40b8-d64d-882f249568d0"},"outputs":[{"name":"stdout","output_type":"stream","text":["Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n","\n","Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n","Running on public URL: https://dbb2efcc3beb268bb9.gradio.live\n","\n","This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"]},{"data":{"text/html":["<div><iframe src=\"https://dbb2efcc3beb268bb9.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"output_type":"display_data"},{"data":{"text/plain":[]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["import gradio as gr\n","\n","input_prompt = gr.Textbox(label = \"Prompt\", value = \"photographer\")\n","input_maxtokens = gr.Textbox(label = \"Max tokens\", value = \"150\")\n","output_component = gr.Textbox(label = \"Output\")\n","examples = [[\"photographer\"], [\"developer\"], [\"teacher\"], [\"human resources staff\"], [\"recipe for ham croquettes\"]]\n","description = \"\"\n","demo = gr.Interface(generatePrompt, inputs = [input_prompt,input_maxtokens], outputs=output_component, examples=examples, title = \"🗿 PerfectGPT v1 🗿\", description=description).launch(share=True)\n","\n","# demo = gr.Interface(fn=useZephyr, inputs=\"text\", outputs=\"text\")\n","\n","demo.launch()"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":2793,"status":"ok","timestamp":1699019750497,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"0VmXXVsJlLVx"},"outputs":[],"source":["%pip freeze > requirements.txt"]}],"metadata":{"accelerator":"GPU","colab":{"authorship_tag":"ABX9TyOAi0penTuWk40HwEr7srEQ","gpuType":"T4","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.11.6"},"widgets":{"application/vnd.jupyter.widget-state+json":{"0170ea53ea47441e846c7469c1e4f23a":{"model_module":"@jupyter-widgets/controls","model_module_version":"1.5.0","model_name":"HBoxModel","state":{"_dom_classes":[],"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"HBoxModel","_view_count":null,"_view_module":"@jupyter-widgets/controls","_view_module_version":"1.5.0","_view_name":"HBoxView","box_style":"","children":["IPY_MODEL_c84203a627284774ab51a47860aa61e0","IPY_MODEL_fa4d8d0270dc41b584409f182c34818e","IPY_MODEL_0dcb667c46cd404aaac4ed26b770b635"],"layout":"IPY_MODEL_ca97c092a79d46cd9d23da559a683df8"}},"021f68515039445483a47f1eff0a508e":{"model_module":"@jupyter-widgets/controls","model_module_version":"1.5.0","model_name":"DescriptionStyleModel","state":{"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"DescriptionStyleModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"StyleView","description_width":""}},"043161d8675c46049b3cc1cb719fa210":{"model_module":"@jupyter-widgets/base","model_module_version":"1.2.0","model_name":"LayoutModel","state":{"_model_module":"@jupyter-widgets/base","_model_module_version":"1.2.0","_model_name":"LayoutModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"LayoutView","align_content":null,"align_items":null,"align_self":null,"border":null,"bottom":null,"display":null,"flex":null,"flex_flow":null,"grid_area":null,"grid_auto_columns":null,"grid_auto_flow":null,"grid_auto_rows":null,"grid_column":null,"grid_gap":null,"grid_row":null,"grid_template_areas":null,"grid_template_columns":null,"grid_template_rows":null,"height":null,"justify_content":null,"justify_items":null,"left":null,"margin":null,"max_height":null,"max_width":null,"min_height":null,"min_width":null,"object_fit":null,"object_position":null,"order":null,"overflow":null,"overflow_x":null,"overflow_y":null,"padding":null,"right":null,"top":null,"visibility":null,"width":null}},"0b54ec51b99b464aae7cb4ef27988fc3":{"model_module":"@jupyter-widgets/controls","model_module_version":"1.5.0","model_name":"HTMLModel","state":{"_dom_classes":[],"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"HTMLModel","_view_count":null,"_view_module":"@jupyter-widgets/controls","_view_module_version":"1.5.0","_view_name":"HTMLView","description":"","description_tooltip":null,"layout":"IPY_MODEL_731358d67c204f4c8847017b98f669e5","placeholder":"​","style":"IPY_MODEL_a2f90e8ab4ea4c67b7a0e255e68ac3b9","value":"Downloading 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6650f491e7","1b2ac0bccd4843b0802540041194ce49","6e5f8339ff64488d8ff275aeb95ab900","9de2ee01c4644e4dbf8934cbfec3aa99","ebec656f034145b0967f3a1753c74060"]},"executionInfo":{"elapsed":308694,"status":"ok","timestamp":1699017517990,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"BHEVUef40Ke8","outputId":"6d967e8d-ebb2-4471-f478-30920898d547"},"outputs":[],"source":["# chatgpt-gpt4-prompts-bart-large-cnn-samsum\n","tokenizer = AutoTokenizer.from_pretrained(\"Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum\")\n","model = AutoModelForSeq2SeqLM.from_pretrained(\"Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum\", from_tf=True)\n","\n","# zephyr\n","pipe = pipeline(\"text-generation\", model=\"HuggingFaceH4/zephyr-7b-alpha\", torch_dtype=torch.bfloat16, device_map=\"auto\")\n","\n","def useZephyr(prompt):\n","    messages = [\n","        {\n","            \"role\": \"system\",\n","            \"content\": \"You are a friendly chatbot who always responds in the style of a pirate.\",\n","        },\n","        {\"role\": \"user\", \"content\": prompt},\n","    ]\n","    # https://huggingface.co/docs/transformers/main/en/chat_templating\n","    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)\n","    \n","    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)\n","    return outputs[0][\"generated_text\"]"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":4,"status":"ok","timestamp":1699017517990,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"pL1isZHpY6DF"},"outputs":[],"source":["def generatePrompt(prompt, max_new_tokens):\n","    batch = tokenizer(prompt, return_tensors=\"pt\")\n","    generated_ids = model.generate(batch[\"input_ids\"], max_new_tokens=int(max_new_tokens))\n","    output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)\n","    prompt = output[0]\n","\n","    return useZephyr(prompt)\n","\n","def generate_test(prompt):\n","    batch = tokenizer(prompt, return_tensors=\"pt\")\n","    generated_ids = model.generate(batch[\"input_ids\"], max_new_tokens=150)\n","    output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)\n","    return output[0]\n","\n","def generate_prompt(prompt, max_new_tokens):\n","      return generatePrompt(prompt, max_new_tokens)\n","#"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":646},"executionInfo":{"elapsed":7653,"status":"ok","timestamp":1699017525641,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"U9q8eO_faoVX","outputId":"67b4e6dc-6b5d-40b8-d64d-882f249568d0"},"outputs":[],"source":["import gradio as gr\n","\n","input_prompt = gr.Textbox(label = \"Prompt\", value = \"photographer\")\n","input_maxtokens = gr.Textbox(label = \"Max tokens\", value = \"150\")\n","output_component = gr.Textbox(label = \"Output\")\n","examples = [[\"photographer\"], [\"developer\"], [\"teacher\"], [\"human resources staff\"], [\"recipe for ham croquettes\"]]\n","description = \"\"\n","demo = gr.Interface(generatePrompt, inputs = [input_prompt,input_maxtokens], outputs=output_component, examples=examples, title = \"🗿 PerfectGPT v1 🗿\", description=description).launch(share=True)\n","\n","# demo = gr.Interface(fn=useZephyr, inputs=\"text\", outputs=\"text\")\n","\n","demo.launch()"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":2793,"status":"ok","timestamp":1699019750497,"user":{"displayName":"Lucas Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"0VmXXVsJlLVx"},"outputs":[],"source":["%pip freeze > requirements.txt"]}],"metadata":{"accelerator":"GPU","colab":{"authorship_tag":"ABX9TyOAi0penTuWk40HwEr7srEQ","gpuType":"T4","provenance":[]},"kernelspec":{"display_name":"Python 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