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Introduction of test_ES
Model Details of test_ES
Model Card for lenu_ES
This model allows to classify
Table of Contents
- Model Card for lenu_ES
- Table of Contents
- Table of Contents
- Model Details
- Uses
- Bias, Risks, and Limitations
- Training Details
- Evaluation
- Model Examination
- Environmental Impact
- Technical Specifications [optional]
- Citation
- Glossary [optional]
- More Information [optional]
- Model Card Authors [optional]
- Model Card Contact
- How to Get Started with the Model
Model Details
Model Description
This model allows to classify
- Developed by: More information needed
- Shared by [Optional]: More information needed
- Model type: Language model
- Language(s) (NLP): es
- License: cc0-1.0
- Parent Model: More information needed
- Resources for more information: More information needed
Uses
Direct Use
Downstream Use [Optional]
Out-of-Scope Use
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
Training Details
Training Data
More information on training data needed
Training Procedure
Preprocessing
More information needed
Speeds, Sizes, Times
More information needed
Evaluation
Testing Data, Factors & Metrics
Testing Data
More information needed
Factors
More information needed
Metrics
More information needed
Results
More information needed
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
More information needed
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]
a, a, r, i, m, o, n, d
Model Card Contact
More information needed
How to Get Started with the Model
Use the code below to get started with the model.
Runs of aarimond test_ES on huggingface.co
More Information About test_ES huggingface.co Model
More test_ES license Visit here:
https://choosealicense.com/licenses/cc0-1.0test_ES huggingface.co
test_ES huggingface.co is an AI model on huggingface.co that provides test_ES's model effect (), which can be used instantly with this aarimond test_ES model. huggingface.co supports a free trial of the test_ES model, and also provides paid use of the test_ES. Support call test_ES model through api, including Node.js, Python, http.
test_ES huggingface.co Url
https://huggingface.co/aarimond/test_ESaarimond test_ES online free
test_ES huggingface.co is an online trial and call api platform, which integrates test_ES's modeling effects, including api services, and provides a free online trial of test_ES, you can try test_ES online for free by clicking the link below.
aarimond test_ES online free url in huggingface.co:
https://huggingface.co/aarimond/test_EStest_ES install
test_ES is an open source model from GitHub that offers a free installation service, and any user can find test_ES on GitHub to install. At the same time, huggingface.co provides the effect of test_ES install, users can directly use test_ES installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
