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Model Details

Model Description

  • Developed by: Manuel Fernández
  • Funded by [optional]: N/A
  • Shared by [optional]: Manuel Fernández
  • Model type: Classification
  • Language(s) (NLP): [More Information Needed]
  • License: [More Information Needed]
  • Finetuned from model [optional]: bert-base-multilingual-cased

Model Sources [optional]

  • Repository: [More Information Needed]
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]

Uses

This model was fined tuned beacuse it is part of course of huggingface about NLP 🤗🤗🤗.

Direct Use

Text Classification

Bias, Risks, and Limitations

Same Bias, Risks and Limitations the model bert-base-multilingual-cased

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

import transformers

tokenizer = transformers.AutoTokenizer.from_pretrained("manyah/bert-base-multilingual-cased-trainer")
model = transformers.AutoModel.from_pretrained("manyah/bert-base-multilingual-cased-trainer")
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Safetensors
Model size
178M params
Tensor type
F32
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Inference Examples
Inference API (serverless) is not available, repository is disabled.