AI model creator details for flax-community

spanish-t5-small

El modelo "spanish-t5-small" es un modelo de lenguaje basado en transformers que ha sido entrenado en una gran cantidad de datos en español. El modelo se puede utilizar para generar texto en español en una variedad de tareas, como generación de resúmenes, traducción automática, respuesta a preguntas, entre otros. Es capaz de generar texto coherente y relevante en español para una amplia gama de aplicaciones.

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153.2K

Huggingface

clip-rsicd-v2

flax-community

The clip-rsicd-v2 model is a zero-shot image classification model. It can classify images based on their content without prior training on specific classes. The model uses the CLIP framework, which combines vision and language understanding to enable versatile and robust image classification. It can provide accurate predictions for a wide range of images and is especially useful when there is limited labeled data available.

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25.2K

Huggingface

gpt-neo-125M-code-clippy-dedup-2048

flax-community

Model Card for gpt-neo-125M-code-clippy-dedup-2048 Model Details Model Description More information needed Developed by: Flax Community Shared by [Optional]: Hugging Face Model type: Text Generation Language(s) (NLP): More information needed License: More information needed Related Models: Parent Model: GPT-Neo Resources for more information: GitHub Repo Uses Direct Use This model can be used for the task of Text Generation Downstream Use [Optional] More information needed Out-of-Scope Use The model should not be used to intentionally create hostile or alienating environments for people. Bias, Risks, and Limitations Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. Recommendations The model creators note in the GitHub Repo](https://github.com/CodedotAl/gpt-code-clippy): Training Details Training Data The model creators note in the GitHub Repo](https://github.com/CodedotAl/gpt-code-clippy): Training Procedure Preprocessing More information needed Speeds, Sizes, Times The model creators note in the GitHub Repo](https://github.com/CodedotAl/gpt-code-clippy): Evaluation Testing Data, Factors & Metrics Testing Data The model creators note in the GitHub Repo](https://github.com/CodedotAl/gpt-code-clippy): Factors More information needed Metrics More information needed Results Model Examination More information needed Environmental Impact Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019). Hardware Type: More information needed Hours used: More information needed Cloud Provider: More information needed Compute Region: More information needed Carbon Emitted: More information needed Technical Specifications [optional] Model Architecture and Objective GPTNeoForCausalLM Compute Infrastructure More information needed Hardware More information needed Software More information needed Citation BibTeX: More information needed APA: More information needed Glossary [optional] More information needed More Information [optional] More information needed Model Card Authors [optional] Flax Community in collaboration with Ezi Ozoani and the Hugging Face team Model Card Contact More information needed How to Get Started with the Model Use the code below to get started with the model.

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2.9K

Huggingface

gpt-2-spanish

flax-community

Platform did not provide a description for this model.

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2.7K

Huggingface

gpt2-medium-persian