tiny-random-albert
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tiny-random-aquila2
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View details ↗tiny-random-aquilachat
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View details ↗tiny-random-ArceeForCausalLM
optimum-intel-internal-testingThis is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed]
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View details ↗tiny-random-ast
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View details ↗tiny-random-aya-base
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View details ↗tiny-random-baichuan2
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View details ↗tiny-random-baichuan2-13b
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View details ↗tiny-random-BeitForImageClassification
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View details ↗tiny-random-bert
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View details ↗tiny-random-bigbird_pegasus
optimum-intel-internal-testingThis is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed]
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View details ↗tiny-random-BioGptForCausalLM
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View details ↗tiny-random-bitnet
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View details ↗tiny-random-BlenderbotModel
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View details ↗tiny-random-BloomModel
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View details ↗tiny-random-camembert
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View details ↗tiny-random-chatglm
optimum-intel-internal-testingThe following hyperparameters were used during training: - learning_rate: 0.0005 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 256 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 1000 - num_epochs: 1
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View details ↗tiny-random-CLIPModel
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View details ↗tiny-random-codegen2
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View details ↗tiny-random-CodeGenForCausalLM
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View details ↗tiny-random-CohereForCausalLM
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View details ↗tiny-random-ConvBertForSequenceClassification
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View details ↗tiny-random-convnext
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View details ↗tiny-random-Data2VecAudioModel
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