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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Машина Времени (Mashina Vremeni).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Mating Ritual.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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text-generation | transformers |
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text-generation | transformers |
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Mnogoznaal.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"##... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repo... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from MORGENSHTERN.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B re... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Мумий Тролль (Mumiy Troll).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the p... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Muse.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Train... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Нервы (Nervy).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Nirvana.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tr... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from OBLADAET.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## T... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from OG Buda.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tr... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from O.T (RUS).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## ... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report."... |
text-generation | transformers |
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Our Last Night.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B ... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Oxxxymiron.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"##... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repo... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Peter, Paul and Mary.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipelin... | [
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"## How does it work?\n\nTo understand how the model was developed, check the... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from PHARAOH.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tr... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Phish.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Trai... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Pink Floyd.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"##... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repo... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Placebo.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tr... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Платина (Platina).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline."... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Post Malone.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"#... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Queen.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Trai... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Radiohead.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## ... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repor... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Ramil’.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tra... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Rammstein.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Red Hot Chili Peppers.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeli... | [
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"## How does it work?\n\nTo understand how the model was developed, check t... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Rex Orange County.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline."... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Rihanna.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tr... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from ROCKET.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tra... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report."... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Sam Kim (샘김).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## How does it work?\n\nTo understand how the model was developed, check the W&B re... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from shadowraze.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"#... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repo... |
text-generation | transformers |
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Skillet.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tr... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-generation | transformers |
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Слава КПСС (Slava KPSS).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipe... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repo... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from SLAVA MARLOW.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B re... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Snoop Dogg.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"##... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repo... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Sqwore.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tra... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report."... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Sugar Ray.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nOr with Transformers library:\n\n\n\nExplore the data, which is tracked with W&B artifacts at... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repor... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Suicideoscope.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nOr with Transformers library:\n\n\n\nExplore the data, which is tracked with W&B artifact... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B r... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Sum 41.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tra... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report."... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from System of a Down.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Танцы Минус (Tanzy Minus).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pi... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Taylor Swift.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B re... |
text-generation | transformers |
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from The 69 Eyes.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"#... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from The Beatles.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"#... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"#... | [
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## How does it work?\n\nTo understand how the model was developed, check the W... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B ... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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text-generation | transformers |
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... | {"language": "en", "tags": ["huggingartists", "lyrics", "lm-head", "causal-lm"], "datasets": ["huggingartists/the-velvet-underground"], "widget": [{"text": "I am"}]} | huggingartists/the-velvet-underground | null | [
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## How does it work?\n\nTo understand how the model was developed, check ... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"##... | [
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"## How does it work?\n\nTo understand how the model was developed, check t... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## Tra... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report."... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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... | [
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Tom Waits.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nOr with Transformers library:\n\n\n\nExplore the data, which is tracked with W&B artifacts at... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B repor... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Тони Раут (Tony Raut) & Гарри Топор (Garry Topor).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts... | [
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"## How does it work?\n\nTo understand how the model was developed, che... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## Train... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"... | [
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text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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"## How does it work?\n\nTo understand how the model was developed, check the W... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from UPSAHL.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## Tra... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report."... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
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... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B re... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Van Morrison.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B re... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from VeggieTales.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"#... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
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"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Виктор Цой (Viktor Tsoi).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pip... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
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<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Владимир Высоцкий (Vladimir Vysotsky).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every st... | [
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"## How does it work?\n\nTo understand how the model was developed, check the W... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/f72572986d8187cf35f0fc9f9d06afb... | {"language": "en", "tags": ["huggingartists", "lyrics", "lm-head", "causal-lm"], "datasets": ["huggingartists/xxxtentacion"], "widget": [{"text": "I am"}]} | huggingartists/xxxtentacion | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm",
"en",
"dataset:huggingartists/xxxtentacion",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingartists #lyrics #lm-head #causal-lm #en #dataset-huggingartists/xxxtentacion #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('URL
</div>
</div>
<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from XXXTENTACION.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"... | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingartists #lyrics #lm-head #causal-lm #en #dataset-huggingartists/xxxtentacion #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## How does it work?\n\nTo understand how the model was developed, check the W&B re... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/8c898f8c39dbd271b3ccfd5303d423c... | {"language": "en", "tags": ["huggingartists", "lyrics", "lm-head", "causal-lm"], "datasets": ["huggingartists/yung-lean"], "widget": [{"text": "I am"}]} | huggingartists/yung-lean | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm",
"en",
"dataset:huggingartists/yung-lean",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingartists #lyrics #lm-head #causal-lm #en #dataset-huggingartists/yung-lean #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('URL
</div>
</div>
<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Yung Lean.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"## ... | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingartists #lyrics #lm-head #causal-lm #en #dataset-huggingartists/yung-lean #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## How does it work?\n\nTo understand how the model was developed, check the W&B repor... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/6c0f8e02f467c694379f242ea2897ef... | {"language": "en", "tags": ["huggingartists", "lyrics", "lm-head", "causal-lm"], "datasets": ["huggingartists/yung-plague"], "widget": [{"text": "I am"}]} | huggingartists/yung-plague | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm",
"en",
"dataset:huggingartists/yung-plague",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingartists #lyrics #lm-head #causal-lm #en #dataset-huggingartists/yung-plague #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('URL
</div>
</div>
<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Yung Plague.\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline.",
"#... | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingartists #lyrics #lm-head #causal-lm #en #dataset-huggingartists/yung-plague #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## How does it work?\n\nTo understand how the model was developed, check the W&B rep... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://images.genius.com/df440220b2dd0a34a119db791da90e5... | {"language": "en", "tags": ["huggingartists", "lyrics", "lm-head", "causal-lm"], "datasets": ["huggingartists/zemfira"], "widget": [{"text": "I am"}]} | huggingartists/zemfira | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingartists",
"lyrics",
"lm-head",
"causal-lm",
"en",
"dataset:huggingartists/zemfira",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingartists #lyrics #lm-head #causal-lm #en #dataset-huggingartists/zemfira #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('URL
</div>
</div>
<div style="text-align:... | [
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on lyrics from Земфира (Zemfira).\n\nDataset is available here.\nAnd can be used with:\n\n\n\nExplore the data, which is tracked with W&B artifacts at every step of the pipeline."... | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingartists #lyrics #lm-head #causal-lm #en #dataset-huggingartists/zemfira #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## How does it work?\n\nTo understand how the model was developed, check the W&B report.... |
text-classification | transformers |
# CodeBERTa-language-id: The World’s fanciest programming language identification algo 🤯
To demonstrate the usefulness of our CodeBERTa pretrained model on downstream tasks beyond language modeling, we fine-tune the [`CodeBERTa-small-v1`](https://huggingface.co/huggingface/CodeBERTa-small-v1) checkpoint on the task... | {"language": "code", "datasets": ["code_search_net"], "thumbnail": "https://cdn-media.huggingface.co/CodeBERTa/CodeBERTa.png"} | huggingface/CodeBERTa-language-id | null | [
"transformers",
"pytorch",
"tf",
"jax",
"rust",
"roberta",
"text-classification",
"code",
"dataset:code_search_net",
"arxiv:1909.09436",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1909.09436"
] | [
"code"
] | TAGS
#transformers #pytorch #tf #jax #rust #roberta #text-classification #code #dataset-code_search_net #arxiv-1909.09436 #autotrain_compatible #endpoints_compatible #region-us
|
# CodeBERTa-language-id: The World’s fanciest programming language identification algo
To demonstrate the usefulness of our CodeBERTa pretrained model on downstream tasks beyond language modeling, we fine-tune the 'CodeBERTa-small-v1' checkpoint on the task of classifying a sample of code into the programming langu... | [
"# CodeBERTa-language-id: The World’s fanciest programming language identification algo \n\n\nTo demonstrate the usefulness of our CodeBERTa pretrained model on downstream tasks beyond language modeling, we fine-tune the 'CodeBERTa-small-v1' checkpoint on the task of classifying a sample of code into the programmin... | [
"TAGS\n#transformers #pytorch #tf #jax #rust #roberta #text-classification #code #dataset-code_search_net #arxiv-1909.09436 #autotrain_compatible #endpoints_compatible #region-us \n",
"# CodeBERTa-language-id: The World’s fanciest programming language identification algo \n\n\nTo demonstrate the usefulness of our... |
fill-mask | transformers |
# CodeBERTa
CodeBERTa is a RoBERTa-like model trained on the [CodeSearchNet](https://github.blog/2019-09-26-introducing-the-codesearchnet-challenge/) dataset from GitHub.
Supported languages:
```shell
"go"
"java"
"javascript"
"php"
"python"
"ruby"
```
The **tokenizer** is a Byte-level BPE tokenizer trained on the ... | {"language": "code", "datasets": ["code_search_net"], "thumbnail": "https://cdn-media.huggingface.co/CodeBERTa/CodeBERTa.png"} | huggingface/CodeBERTa-small-v1 | null | [
"transformers",
"pytorch",
"tf",
"jax",
"roberta",
"fill-mask",
"code",
"dataset:code_search_net",
"arxiv:1909.09436",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [
"1909.09436"
] | [
"code"
] | TAGS
#transformers #pytorch #tf #jax #roberta #fill-mask #code #dataset-code_search_net #arxiv-1909.09436 #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# CodeBERTa
CodeBERTa is a RoBERTa-like model trained on the CodeSearchNet dataset from GitHub.
Supported languages:
The tokenizer is a Byte-level BPE tokenizer trained on the corpus using Hugging Face 'tokenizers'.
Because it is trained on a corpus of code (vs. natural language), it encodes the corpus efficient... | [
"# CodeBERTa\n\nCodeBERTa is a RoBERTa-like model trained on the CodeSearchNet dataset from GitHub.\n\nSupported languages:\n\n\n\nThe tokenizer is a Byte-level BPE tokenizer trained on the corpus using Hugging Face 'tokenizers'.\n\nBecause it is trained on a corpus of code (vs. natural language), it encodes the co... | [
"TAGS\n#transformers #pytorch #tf #jax #roberta #fill-mask #code #dataset-code_search_net #arxiv-1909.09436 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# CodeBERTa\n\nCodeBERTa is a RoBERTa-like model trained on the CodeSearchNet dataset from GitHub.\n\nSupported languages:\n\n\n\nThe ... |
null | null |
The purpose of this repo is to show the usefulness of saving the normalization operation used during the tokenizer training
```python
from transformers import AutoTokenizer
text = "This is a text with àccënts and CAPITAL LETTERS"
tokenizer = AutoTokenizer.from_pretrained("albert-large-v2")
print(tokenizer.convert_id... | {} | huggingface-course/albert-tokenizer-without-normalizer | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
|
The purpose of this repo is to show the usefulness of saving the normalization operation used during the tokenizer training
| [] | [
"TAGS\n#region-us \n"
] |
token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# test-bert-finetuned-ner
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the c... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "test-bert-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type... | huggingface-course/bert-finetuned-ner | null | [
"transformers",
"pytorch",
"tf",
"tensorboard",
"bert",
"token-classification",
"generated_from_trainer",
"dataset:conll2003",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
| test-bert-finetuned-ner
=======================
This model is a fine-tuned version of bert-base-cased on the conll2003 dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0600
* Precision: 0.9355
* Recall: 0.9514
* F1: 0.9433
* Accuracy: 0.9868
Model description
-----------------
More in... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
"### Training... | [
"TAGS\n#transformers #pytorch #tf #tensorboard #bert #token-classification #generated_from_trainer #dataset-conll2003 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\... |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# test-bert-finetuned-squad
This model was trained from scratch on the squad dataset.
## Model description
More information need... | {"tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "test-bert-finetuned-squad", "results": []}]} | huggingface-course/bert-finetuned-squad | null | [
"transformers",
"pytorch",
"tf",
"tensorboard",
"bert",
"question-answering",
"generated_from_trainer",
"dataset:squad",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #tensorboard #bert #question-answering #generated_from_trainer #dataset-squad #endpoints_compatible #has_space #region-us
|
# test-bert-finetuned-squad
This model was trained from scratch on the squad dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following ... | [
"# test-bert-finetuned-squad\n\nThis model was trained from scratch on the squad dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Training procedure",
"### Training h... | [
"TAGS\n#transformers #pytorch #tf #tensorboard #bert #question-answering #generated_from_trainer #dataset-squad #endpoints_compatible #has_space #region-us \n",
"# test-bert-finetuned-squad\n\nThis model was trained from scratch on the squad dataset.",
"## Model description\n\nMore information needed",
"## In... |
fill-mask | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased-finetuned-imdb
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imdb"], "model-index": [{"name": "distilbert-base-uncased-finetuned-imdb", "results": []}]} | huggingface-course/distilbert-base-uncased-finetuned-imdb | null | [
"transformers",
"pytorch",
"tf",
"tensorboard",
"distilbert",
"fill-mask",
"generated_from_trainer",
"dataset:imdb",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #tensorboard #distilbert #fill-mask #generated_from_trainer #dataset-imdb #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us
| distilbert-base-uncased-finetuned-imdb
======================================
This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset.
It achieves the following results on the evaluation set:
* Loss: 2.4264
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 64\n* eval\\_batch\\_size: 64\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3.0\n* mixed\\_pr... | [
"TAGS\n#transformers #pytorch #tf #tensorboard #distilbert #fill-mask #generated_from_trainer #dataset-imdb #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate:... |
translation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# test-marian-finetuned-kde4-en-to-fr
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/He... | {"license": "apache-2.0", "tags": ["translation", "generated_from_trainer"], "datasets": ["kde4"], "metrics": ["bleu"], "model-index": [{"name": "test-marian-finetuned-kde4-en-to-fr", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "kde4", "ty... | huggingface-course/marian-finetuned-kde4-en-to-fr | null | [
"transformers",
"pytorch",
"tf",
"tensorboard",
"marian",
"text2text-generation",
"translation",
"generated_from_trainer",
"dataset:kde4",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #tensorboard #marian #text2text-generation #translation #generated_from_trainer #dataset-kde4 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us
|
# test-marian-finetuned-kde4-en-to-fr
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-fr on the kde4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8559
- Bleu: 52.9416
## Model description
More information needed
## Intended uses & limitations
More information needed
... | [
"# test-marian-finetuned-kde4-en-to-fr\n\nThis model is a fine-tuned version of Helsinki-NLP/opus-mt-en-fr on the kde4 dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 0.8559\n- Bleu: 52.9416",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore ... | [
"TAGS\n#transformers #pytorch #tf #tensorboard #marian #text2text-generation #translation #generated_from_trainer #dataset-kde4 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us \n",
"# test-marian-finetuned-kde4-en-to-fr\n\nThis model is a fine-tuned version of He... |
summarization | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mt5-finetuned-amazon-en-es
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on ... | {"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "base_model": "google/mt5-small", "model-index": [{"name": "mt5-finetuned-amazon-en-es", "results": []}]} | huggingface-course/mt5-finetuned-amazon-en-es | null | [
"transformers",
"pytorch",
"tensorboard",
"mt5",
"text2text-generation",
"summarization",
"generated_from_trainer",
"base_model:google/mt5-small",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #base_model-google/mt5-small #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| mt5-finetuned-amazon-en-es
==========================
This model is a fine-tuned version of google/mt5-small on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 3.0285
* Rouge1: 16.9728
* Rouge2: 8.2969
* Rougel: 16.8366
* Rougelsum: 16.851
* Gen Len: 10.1597
Model description
--... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 5.6e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 8",
"### Traini... | [
"TAGS\n#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #base_model-google/mt5-small #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were... |
summarization | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-smal... | {"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-amazon-en-es", "results": []}]} | huggingface-course/mt5-small-finetuned-amazon-en-es | null | [
"transformers",
"pytorch",
"tf",
"tensorboard",
"mt5",
"text2text-generation",
"summarization",
"generated_from_trainer",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"has_space",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#transformers #pytorch #tf #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us
| mt5-small-finetuned-amazon-en-es
================================
This model is a fine-tuned version of google/mt5-small on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 3.0285
* Rouge1: 16.9728
* Rouge2: 8.2969
* Rougel: 16.8366
* Rougelsum: 16.8510
* Gen Len: 10.1597
Model d... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 8e-05\n* train\\_batch\\_size: 8\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 8",
"### Training... | [
"TAGS\n#transformers #pytorch #tf #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us \n",
"### Training hyperparameters\n\n\nThe following hyperparameters were used during t... |
null | null | #ifdef GL_ES
precision highp float;
#endif
#define pi2_inv 0.0
uniform float time;
uniform vec2 resolution;
float border(vec2 uv, float thickness){
uv = fract(uv - vec2(0.5));
uv = min(uv, vec2(1.)-uv)*2.;
// return 1./length(uv-0.5)-thickness;
return clamp(max(uv.x,uv.x)-1.+thickness,0.,1.)/thickness;;
}
vec2 div... | {} | hugginglol/no | null | [
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [] | TAGS
#region-us
| #ifdef GL_ES
precision highp float;
#endif
#define pi2_inv 0.0
uniform float time;
uniform vec2 resolution;
float border(vec2 uv, float thickness){
uv = fract(uv - vec2(0.5));
uv = min(uv, vec2(1.)-uv)*2.;
// return 1./length(uv-0.5)-thickness;
return clamp(max(uv.x,uv.x)-1.+thickness,0.,1.)/thickness;;
}
vec2 div... | [] | [
"TAGS\n#region-us \n"
] |
text-generation | transformers |
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1363688455352553473/nfQUoTBH_400x400.jpg')">
</div>
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">kn 🤖 AI Bot </div>
<div style="font-size: 15px">@09i... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/09indierock/1616791178582/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/09indierock | null | [
"transformers",
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"jax",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
kn AI Bot
@09indierock bot
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
-------------
The ... | [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1427911499083886600/byWM... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/0xtuba-jacksondame-mikedemarais/1631855884132/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/0xtuba-jacksondame-mikedemarais | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI CYBORG
URL & URL & tuba
@0xtuba-jacksondame-mikedemarais
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1377780722883174400/4gq8ntlP_400x400.jpg')">
</div>
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">parallellax 🤖 AI Bot </div>
<div style="font-size: 1... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/12123i123i12345/1617760753400/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/12123i123i12345 | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
parallellax AI Bot
@12123i123i12345 bot
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
-------... | [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1292932868121993222/Ifd5... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/12rafiqul/1629189930683/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/12rafiqul | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
Sk Rafiqul Islam
@12rafiqul
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
----... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1236431647576330246/GGaeVBZJ_400x400.jpg')">
</div>
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">mon nom non-mo 🤖 AI Bot </div>
<div style="font-size... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/14jun1995/1616669363048/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/14jun1995 | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
mon nom non-mo AI Bot
@14jun1995 bot
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
----------... | [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1343113335882063873/mITxI5OI_400x400.jpg')">
</div>
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">SIKA MODE | BLM 🤖 AI Bot </div>
<div style="font-siz... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/14werewolfvevo/1617769919321/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/14werewolfvevo | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
SIKA MODE | BLM AI Bot
@14werewolfvevo bot
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
----... | [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">
<style>
@media (prefers-color-scheme: dark) {
.prose { color: #E2E8F0 !important; }
.prose h2, .prose h3, .prose a, .prose thead { color: #F7FAFC !important; }
}
</style>
<section class='prose'>
<div>
<div sty... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/178kakapo/1603720462678/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/178kakapo | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
<link rel="stylesheet" href="URL
<style>
@media (prefers-color-scheme: dark) {
.prose { color: #E2E8F0 !important; }
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}
</style>
<section class='prose'>
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: c... | [
"## How does it work?\n\nThe model uses the following pipeline.\n\n!pipeline\n\nTo understand how the model was developed, check the W&B report.",
"## Training data\n\nThe model was trained on @178kakapo's tweets.\n\n<table style='border-width:0'>\n<thead style='border-width:0'>\n<tr style='border-width:0 0 1px 0... | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"## How does it work?\n\nThe model uses the following pipeline.\n\n!pipeline\n\nTo understand how the model was developed, check the W&B report.",
"... |
text-generation | transformers |
<div class="inline-flex flex-col" style="line-height: 1.5;">
<div class="flex">
<div
style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1441261735004966923/Slec... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/2wyatt2mason/1635723936956/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/2wyatt2mason | null | [
"transformers",
"pytorch",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
AI BOT
di!!! ️
@2wyatt2mason
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
-----------... | [] | [
"TAGS\n#transformers #pytorch #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1372571751817744388/tQ01SZ4b_400x400.jpg')">
</div>
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Homo🍄Ludens 🤖 AI Bot </div>
<div style="font-size: ... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/3lliethedoll/1617760689416/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/3lliethedoll | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
HomoLudens AI Bot
@3lliethedoll bot
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
-----------... | [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1371476407767957505/xfhZ00Hv_400x400.jpg')">
</div>
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Jeremy Spradlin 🤖 AI Bot </div>
<div style="font-siz... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/3rbunn1nja/1616808238654/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/3rbunn1nja | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
Jeremy Spradlin AI Bot
@3rbunn1nja bot
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data
--------... | [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
text-generation | transformers |
<div>
<div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1296604630537961476/BGjTffM9_400x400.jpg')">
</div>
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">🔥3thanguy7 is from chicago 🤖 AI Bot </div>
<div sty... | {"language": "en", "tags": ["huggingtweets"], "thumbnail": "https://www.huggingtweets.com/3thanguy7/1614103760144/predictions.png", "widget": [{"text": "My dream is"}]} | huggingtweets/3thanguy7 | null | [
"transformers",
"pytorch",
"jax",
"gpt2",
"text-generation",
"huggingtweets",
"en",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2022-03-02T23:29:05+00:00 | [] | [
"en"
] | TAGS
#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
3thanguy7 is from chicago AI Bot
@3thanguy7 bot
I was made with huggingtweets.
Create your own bot based on your favorite user with the demo!
How does it work?
-----------------
The model uses the following pipeline.
!pipeline
To understand how the model was developed, check the W&B report.
Training data... | [] | [
"TAGS\n#transformers #pytorch #jax #gpt2 #text-generation #huggingtweets #en #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n"
] |
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