---
license: other
language:
- en
- ko
- zh
- fr
library_name: fasttext
pipeline_tag: text-classification
---
# Open fasttext LangID models

<!-- Provide a quick summary of what the model is/does. -->

This repo makes readily available several fasttext based open langID models.
While the use and distribution of this collection itself is available according to Apache 2.0, 
but individual models maybe under different more stringent licenses and end users MUST ensure the licenses before distribution or usage.

Quantized versions have been derived by the author  [Chris Ha](hac541309@gmail.com)

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->



- **Developed by:** [Individual Developers]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [Fasttext Classifier]
- **Language(s) (NLP):** [Multilingual]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [Individual models]

### Model Source for lid.176

<!-- Provide the basic links for the model. -->

- **Repository:** [FastText 176](https://fasttext.cc/docs/en/language-identification.html)
- **Paper :** [An Open Dataset and Model for Language Identification](https://arxiv.org/abs/2305.13820)
- **Languages :** 176
- **Filesize :** 938013 bytes
- **SHA-384 :** 574c310c8d82540a8765d28140bf3e6cd01ceb7d164c9ec205c518254bfa0333ae1b80aab7ceff56e7159eced98a3d37

### Model Source for OpenLID

<!-- Provide the basic links for the model. -->

- **Repository:** [An Open Dataset and Model for Language Identification](https://github.com/laurieburchell/open-lid-dataset)
- **Paper [optional]:** [An Open Dataset and Model for Language Identification](https://arxiv.org/abs/2305.13820)
- **Languages :** 201
- **Filesize :** 158024393 bytes
- **SHA-384 :** 99b86a2121f71fdfd801715ed19a09e5e1eee42c2f0bc6340c6aa40dd737757346733a87be130091bc01c4976973d250

### Model Source for NLLB langID(lid218e)

<!-- Provide the basic links for the model. -->

- **Repository:** [fastText (Language Identification)](https://huggingface.co/facebook/fasttext-language-identification)
- **Paper [optional]:** [No Language Left Behind: Scaling Human-Centered Machine Translation](https://arxiv.org/abs/2207.04672)
- **Demo [optional]:** [More Information Needed]
- **Languages :** 218
- **Filesize :** 149855754 bytes
- **SHA-384 :** a6fda88d22d2228b0beb6025ccde5da582ec8eb6679a57f4b3794b127658749653c7d6db8a17fcbe2f86c9678b20ae9f

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
Language Classification

### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
Language Classification

[More Information Needed]

### Downstream Use [optional]

<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
Refer to details of each model
[More Information Needed]

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
Refer to details of each model
[More Information Needed]

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->
Refer to details of each model
[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

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.

[More Information Needed]

## Training Details

### Training Data

<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

[More Information Needed]

### Training Procedure 

<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->

#### Preprocessing [optional]

[More Information Needed]


#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

[More Information Needed]

## Evaluation

<!-- This section describes the evaluation protocols and provides the results. -->

### Testing Data, Factors & Metrics

#### Testing Data

<!-- This should link to a Data Card if possible. -->

[More Information Needed]

#### Factors

<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->

[More Information Needed]

#### Metrics

<!-- These are the evaluation metrics being used, ideally with a description of why. -->

[More Information Needed]

### Results

[More Information Needed]

#### Summary



## Model Examination [optional]

<!-- Relevant interpretability work for the model goes here -->

[More Information Needed]

## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **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 [optional]

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

[More Information Needed]

**APA:**

[More Information Needed]

## Glossary [optional]

<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->

[More Information Needed]

## More Information [optional]

[More Information Needed]

## Model Card Authors [optional]

[More Information Needed]

## Model Card Contact

[More Information Needed]