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wheels for collected packages: transformers, ffmpy\n","  Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for transformers: filename=transformers-4.36.0.dev0-py3-none-any.whl size=7920934 sha256=b2a49950e9f99953136f48acaf046deabe803d97713625bdc90534382ea1b14a\n","  Stored in directory: /tmp/pip-ephem-wheel-cache-9fw4m5vv/wheels/d9/3d/ab/28ae056a634730dae1213fc3321afc3fc1d207699fe3f889cf\n","  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5579 sha256=5d975bf1c41796de7ee85ddd71f270536323e25a0045313de8ce1eafa03015ab\n","  Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\n","Successfully built transformers ffmpy\n","Installing collected packages: pydub, ffmpy, websockets, typing-extensions, tomlkit, shellingham, semantic-version, safetensors, python-multipart, orjson, h11, colorama, annotated-types, aiofiles, uvicorn, starlette, pydantic-core, huggingface-hub, httpcore, tokenizers, pydantic, httpx, diffusers, accelerate, transformers, gradio-client, fastapi, gradio\n","  Attempting uninstall: typing-extensions\n","    Found existing installation: typing_extensions 4.5.0\n","    Uninstalling typing_extensions-4.5.0:\n","      Successfully uninstalled typing_extensions-4.5.0\n","  Attempting uninstall: pydantic\n","    Found existing installation: pydantic 1.10.13\n","    Uninstalling pydantic-1.10.13:\n","      Successfully uninstalled pydantic-1.10.13\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","lida 0.0.10 requires kaleido, which is not installed.\n","llmx 0.0.15a0 requires cohere, which is not installed.\n","llmx 0.0.15a0 requires openai, which is not installed.\n","llmx 0.0.15a0 requires tiktoken, which is not installed.\n","tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.\u001b[0m\u001b[31m\n","\u001b[0mSuccessfully installed accelerate-0.24.1 aiofiles-23.2.1 annotated-types-0.6.0 colorama-0.4.6 diffusers-0.21.4 fastapi-0.104.1 ffmpy-0.3.1 gradio-4.0.2 gradio-client-0.7.0 h11-0.14.0 httpcore-0.18.0 httpx-0.25.0 huggingface-hub-0.17.3 orjson-3.9.10 pydantic-2.4.2 pydantic-core-2.10.1 pydub-0.25.1 python-multipart-0.0.6 safetensors-0.4.0 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.27.0 tokenizers-0.14.1 tomlkit-0.12.0 transformers-4.36.0.dev0 typing-extensions-4.8.0 uvicorn-0.23.2 websockets-11.0.3\n"]}],"source":["%pip install accelerate gradio torch torchvision diffusers git+https://github.com/huggingface/transformers@main"]},{"cell_type":"code","execution_count":2,"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"]},{"cell_type":"code","execution_count":3,"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","75cf764dabfc4a9ca9869318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Ruiz","userId":"18227400269330035369"},"user_tz":-60},"id":"BHEVUef40Ke8","outputId":"6d967e8d-ebb2-4471-f478-30920898d547"},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"7d1e457e201440d88b4a1a9daeb38caf","version_major":2,"version_minor":0},"text/plain":["Downloading (…)okenizer_config.json:   0%|          | 0.00/1.33k [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"1e594c0b7feb4678ac7b840795c8e7f1","version_major":2,"version_minor":0},"text/plain":["Downloading (…)olve/main/vocab.json:   0%|          | 0.00/798k [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"c3ad38bc4b124a56a6c06a831f890ed1","version_major":2,"version_minor":0},"text/plain":["Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, 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?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"7b97e616d938448b8053bea5f46c7e64","version_major":2,"version_minor":0},"text/plain":["Downloading (…)/main/tokenizer.json:   0%|          | 0.00/1.80M [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"6edba32d561c44d48b89d937954ba551","version_major":2,"version_minor":0},"text/plain":["Downloading (…)in/added_tokens.json:   0%|          | 0.00/42.0 [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"abebfd20d346469c975f5afa408b2b7d","version_major":2,"version_minor":0},"text/plain":["Downloading (…)cial_tokens_map.json:   0%|          | 0.00/168 [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"}],"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","    print(prompt)\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":4,"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":5,"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(useZephyr, 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":7,"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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