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keras-io (Keras)
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Keras.io
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Push your Keras models to Hub ❤️
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Find all Keras models on the 🤗 Hub
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\n Welcome to the Keras Working Group where we reproduce Keras examples and build demos to them! 🤗❤️ See our work in this page ✨\n

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Keras.io
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\n \"\"\n
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Push your Keras models to Hub ❤️
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\n \"\"\n
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Find all Keras models on the 🤗 Hub
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\n \n
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ce.co/v1/production/uploads/1639410947738-6141a88b3a0ec78603c9e784.png","fullname":"Keras","name":"keras-io","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":290,"isUserFollowing":false},"downloads":16,"gated":false,"id":"keras-io/timeseries_transformer_classification","availableInferenceProviders":[],"lastModified":"2024-07-09T13:35:48.000Z","likes":13,"pipeline_tag":"time-series-forecasting","private":false,"repoType":"model","isLikedByUser":false},{"author":"keras-io","authorData":{"_id":"61b76d1d9f7cfeae618e726e","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1639410947738-6141a88b3a0ec78603c9e784.png","fullname":"Keras","name":"keras-io","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":290,"isUserFollowing":false},"downloads":323,"gated":false,"id":"keras-io/monocular-depth-estimation","availableInferenceProviders":[],"lastModified":"2024-07-09T13:35:37.000Z","likes":16,"private":false,"repoType":"model","isLikedByUser":false}],"paperPreviews":[],"spaces":[{"author":"keras-io","authorData":{"_id":"61b76d1d9f7cfeae618e726e","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1639410947738-6141a88b3a0ec78603c9e784.png","fullname":"Keras","name":"keras-io","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":290,"isUserFollowing":false},"colorFrom":"green","colorTo":"blue","createdAt":"2022-06-11T07:42:21.000Z","emoji":"📊","id":"keras-io/english-speaker-accent-recognition-using-transfer-learning","lastModified":"2024-10-02T12:49:07.000Z","likes":1,"pinned":false,"private":false,"sdk":"gradio","repoType":"space","runtime":{"stage":"RUNNING","hardware":{"current":"cpu-upgrade","requested":"cpu-upgrade"},"storage":null,"gcTimeout":null,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"keras-io-english-speaker-accent-recognition-usin-a360bef.hf.space","stage":"READY"}],"sha":"a3d8c34f9092eaca920442656a62971fffcbe9a7"},"title":"English Speaker Accent Recognition Using Transfer Learning","isLikedByUser":false,"ai_short_description":"Identify English accents from audio recordings","ai_category":"Speech Synthesis","trendingScore":0,"tags":["gradio","region:us"],"featured":false},{"author":"keras-io","authorData":{"_id":"61b76d1d9f7cfeae618e726e","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1639410947738-6141a88b3a0ec78603c9e784.png","fullname":"Keras","name":"keras-io","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":290,"isUserFollowing":false},"colorFrom":"red","colorTo":"blue","createdAt":"2022-07-07T08:21:07.000Z","emoji":"🌇🌆","id":"keras-io/bert-semantic-similarity","lastModified":"2024-06-07T14:40:02.000Z","likes":23,"pinned":false,"private":false,"sdk":"gradio","repoType":"space","runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"cpu-upgrade"},"storage":null,"gcTimeout":null,"errorMessage":"Traceback (most recent call last):\n File \"/home/user/app/app.py\", line 1, in \n from huggingface_hub import from_pretrained_keras\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/__init__.py\", line 503, in __getattr__\n submod = importlib.import_module(submod_path)\n File \"/usr/local/lib/python3.10/importlib/__init__.py\", line 126, in import_module\n return _bootstrap._gcd_import(name[level:], package, level)\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/keras_mixin.py\", line 10, in \n from huggingface_hub import ModelHubMixin, snapshot_download\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/__init__.py\", line 503, in __getattr__\n submod = importlib.import_module(submod_path)\n File \"/usr/local/lib/python3.10/importlib/__init__.py\", line 126, in import_module\n return _bootstrap._gcd_import(name[level:], package, level)\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/hub_mixin.py\", line 31, in \n from safetensors.torch import load_model as load_model_as_safetensor\n File \"/usr/local/lib/python3.10/site-packages/safetensors/torch.py\", line 6, in \n import torch\nModuleNotFoundError: No module named 'torch'\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"keras-io-bert-semantic-similarity.hf.space","stage":"READY"}]},"title":"Semantic Similarity with BERT","isLikedByUser":false,"trendingScore":0,"tags":["gradio","region:us"],"featured":true},{"author":"keras-io","authorData":{"_id":"61b76d1d9f7cfeae618e726e","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1639410947738-6141a88b3a0ec78603c9e784.png","fullname":"Keras","name":"keras-io","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":290,"isUserFollowing":false},"colorFrom":"red","colorTo":"green","createdAt":"2022-07-07T07:30:20.000Z","emoji":"🔦","id":"keras-io/dual-encoder-image-search","lastModified":"2024-06-07T14:39:34.000Z","likes":10,"pinned":false,"private":false,"sdk":"gradio","repoType":"space","runtime":{"stage":"BUILD_ERROR","hardware":{"current":null,"requested":"cpu-upgrade"},"storage":null,"gcTimeout":null,"errorMessage":"Build failed with exit code: 1","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"keras-io-dual-encoder-image-search.hf.space","stage":"READY"}]},"title":"Natural language image search with a Dual Encoder","isLikedByUser":false,"trendingScore":0,"tags":["gradio","region:us"],"featured":true},{"author":"keras-io","authorData":{"_id":"61b76d1d9f7cfeae618e726e","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1639410947738-6141a88b3a0ec78603c9e784.png","fullname":"Keras","name":"keras-io","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":290,"isUserFollowing":false},"colorFrom":"green","colorTo":"green","createdAt":"2022-06-29T14:34:33.000Z","emoji":"🌹💨","id":"keras-io/denoising-diffusion-implicit-models","lastModified":"2024-06-07T14:38:45.000Z","likes":9,"pinned":false,"private":false,"sdk":"gradio","repoType":"space","runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"cpu-upgrade"},"storage":null,"gcTimeout":null,"errorMessage":": I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\nTo enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n2024-06-07 16:39:22.144435: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\nTraceback (most recent call last):\n File \"/home/user/app/app.py\", line 11, in \n model = hf_hub.from_pretrained_keras(\"keras-io/denoising-diffusion-implicit-models\")\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/keras_mixin.py\", line 293, in from_pretrained_keras\n return KerasModelHubMixin.from_pretrained(*args, **kwargs)\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py\", line 114, in _inner_fn\n return fn(*args, **kwargs)\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/hub_mixin.py\", line 511, in from_pretrained\n instance = cls._from_pretrained(\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/keras_mixin.py\", line 494, in _from_pretrained\n model = keras.models.load_model(storage_folder)\n File \"/usr/local/lib/python3.10/site-packages/keras/src/saving/saving_api.py\", line 193, in load_model\n raise ValueError(\nValueError: File format not supported: filepath=/home/user/.cache/huggingface/hub/models--keras-io--denoising-diffusion-implicit-models/snapshots/5efce4d509350617b3239a2ca0f5f18b288ba6aa. Keras 3 only supports V3 `.keras` files and legacy H5 format files (`.h5` extension). Note that the legacy SavedModel format is not supported by `load_model()` in Keras 3. In order to reload a TensorFlow SavedModel as an inference-only layer in Keras 3, use `keras.layers.TFSMLayer(/home/user/.cache/huggingface/hub/models--keras-io--denoising-diffusion-implicit-models/snapshots/5efce4d509350617b3239a2ca0f5f18b288ba6aa, call_endpoint='serving_default')` (note that your `call_endpoint` might have a different name).\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"keras-io-denoising-diffusion-implicit-models.hf.space","stage":"READY"}]},"title":"Denoising Diffusion Implicit Models","isLikedByUser":false,"trendingScore":0,"tags":["gradio","region:us"],"featured":true},{"author":"keras-io","authorData":{"_id":"61b76d1d9f7cfeae618e726e","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1639410947738-6141a88b3a0ec78603c9e784.png","fullname":"Keras","name":"keras-io","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":290,"isUserFollowing":false},"colorFrom":"green","colorTo":"red","createdAt":"2022-06-25T15:38:03.000Z","emoji":"🌍","id":"keras-io/timeseries-classification-from-scratch","lastModified":"2024-06-07T14:38:16.000Z","likes":2,"pinned":false,"private":false,"sdk":"gradio","repoType":"space","runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"cpu-upgrade"},"storage":null,"gcTimeout":null,"errorMessage":"I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\nTo enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n2024-06-07 16:39:58.837128: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\nTraceback (most recent call last):\n File \"/home/user/app/app.py\", line 15, in \n model = from_pretrained_keras(\"keras-io/timeseries-classification-from-scratch\")\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/keras_mixin.py\", line 293, in from_pretrained_keras\n return KerasModelHubMixin.from_pretrained(*args, **kwargs)\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py\", line 114, in _inner_fn\n return fn(*args, **kwargs)\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/hub_mixin.py\", line 511, in from_pretrained\n instance = cls._from_pretrained(\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/keras_mixin.py\", line 494, in _from_pretrained\n model = keras.models.load_model(storage_folder)\n File \"/usr/local/lib/python3.10/site-packages/keras/src/saving/saving_api.py\", line 193, in load_model\n raise ValueError(\nValueError: File format not supported: filepath=/home/user/.cache/huggingface/hub/models--keras-io--timeseries-classification-from-scratch/snapshots/c311a7c57aa667d1cdbaf103105aea5b64b622f5. Keras 3 only supports V3 `.keras` files and legacy H5 format files (`.h5` extension). Note that the legacy SavedModel format is not supported by `load_model()` in Keras 3. In order to reload a TensorFlow SavedModel as an inference-only layer in Keras 3, use `keras.layers.TFSMLayer(/home/user/.cache/huggingface/hub/models--keras-io--timeseries-classification-from-scratch/snapshots/c311a7c57aa667d1cdbaf103105aea5b64b622f5, call_endpoint='serving_default')` (note that your `call_endpoint` might have a different name).\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"keras-io-timeseries-classification-from-scratch.hf.space","stage":"READY"}]},"title":"Timeseries Classification From Scratch","isLikedByUser":false,"trendingScore":0,"tags":["gradio","region:us"],"featured":true},{"author":"keras-io","authorData":{"_id":"61b76d1d9f7cfeae618e726e","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/1639410947738-6141a88b3a0ec78603c9e784.png","fullname":"Keras","name":"keras-io","type":"org","isHf":false,"isHfAdmin":false,"isMod":false,"followerCount":290,"isUserFollowing":false},"colorFrom":"green","colorTo":"yellow","createdAt":"2022-06-15T21:39:53.000Z","emoji":"⚗️","id":"keras-io/adamatch-domain-adaption","lastModified":"2024-06-07T14:35:44.000Z","likes":1,"pinned":false,"private":false,"sdk":"gradio","repoType":"space","runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"cpu-upgrade"},"storage":null,"gcTimeout":null,"errorMessage":"used.\n2024-06-07 16:37:17.505043: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\nTo enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n2024-06-07 16:37:18.446627: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\nTraceback (most recent call last):\n File \"/home/user/app/app.py\", line 6, in \n adamatch_model = from_pretrained_keras(\"keras-io/adamatch-domain-adaption\")\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/keras_mixin.py\", line 293, in from_pretrained_keras\n return KerasModelHubMixin.from_pretrained(*args, **kwargs)\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py\", line 114, in _inner_fn\n return fn(*args, **kwargs)\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/hub_mixin.py\", line 511, in from_pretrained\n instance = cls._from_pretrained(\n File \"/usr/local/lib/python3.10/site-packages/huggingface_hub/keras_mixin.py\", line 494, in _from_pretrained\n model = keras.models.load_model(storage_folder)\n File \"/usr/local/lib/python3.10/site-packages/keras/src/saving/saving_api.py\", line 193, in load_model\n raise ValueError(\nValueError: File format not supported: filepath=/home/user/.cache/huggingface/hub/models--keras-io--adamatch-domain-adaption/snapshots/7557692a60ba522ecfeb9a1b8e1b3789dd94bef1. Keras 3 only supports V3 `.keras` files and legacy H5 format files (`.h5` extension). Note that the legacy SavedModel format is not supported by `load_model()` in Keras 3. In order to reload a TensorFlow SavedModel as an inference-only layer in Keras 3, use `keras.layers.TFSMLayer(/home/user/.cache/huggingface/hub/models--keras-io--adamatch-domain-adaption/snapshots/7557692a60ba522ecfeb9a1b8e1b3789dd94bef1, call_endpoint='serving_default')` (note that your `call_endpoint` might have a different name).\n","replicas":{"requested":1},"devMode":false,"domains":[{"domain":"keras-io-adamatch-domain-adaption.hf.space","stage":"READY"}]},"title":"AdaMatch Semi-Supervised Domain Adaption","isLikedByUser":false,"trendingScore":0,"tags":["gradio","region:us"],"featured":false}],"buckets":[],"numBuckets":0,"numDatasets":0,"numModels":104,"numSpaces":86,"lastOrgActivities":[],"acceptLanguages":["*"],"canReadRepos":false,"canReadSpaces":false,"blogPosts":[],"currentRepoPage":0,"filters":{},"paperView":false}">

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