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added multiple model_cards for below models (#6666)
* Create README.md * Update README.md * Create README.md * Update README.md * added multiple codeswitch model
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# codeswitch-hineng-lid-lince
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This is a pretrained model for **language identification** of `hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
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## Identify Language
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* Method-1
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---
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language:
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- hi
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- en
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---
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# codeswitch-hineng-ner-lince
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This is a pretrained model for **Name Entity Recognition** of `Hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
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This model is trained for this below repository.
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[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
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To install codeswitch:
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```
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pip install codeswitch
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```
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## Identify Language
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* Method-1
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```py
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince")
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model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince")
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ner_model = pipeline('ner', model=model, tokenizer=tokenizer)
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ner_model("put any hindi english code-mixed sentence")
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```
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* Method-2
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```py
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from codeswitch.codeswitch import NER
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ner = NER('hin-eng')
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text = "" # your mixed sentence
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result = ner.tag(text)
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print(result)
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```
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---
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language:
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- hi
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- en
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---
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# codeswitch-hineng-pos-lince
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This is a pretrained model for **Part of Speech Tagging** of `hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
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This model is trained for this below repository.
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[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
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To install codeswitch:
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```
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pip install codeswitch
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```
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## Identify Language
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* Method-1
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```py
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-pos-lince")
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model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-hineng-pos-lince")
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pos_model = pipeline('ner', model=model, tokenizer=tokenizer)
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pos_model("put any hindi english code-mixed sentence")
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```
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* Method-2
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```py
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from codeswitch.codeswitch import POS
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pos = POS('hin-eng')
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text = "" # your mixed sentence
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result = pos.tag(text)
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print(result)
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```
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---
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language:
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- ne
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- en
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---
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# codeswitch-nepeng-lid-lince
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This is a pretrained model for **language identification** of `nepali-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home).
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This model is trained for this below repository.
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[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
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To install codeswitch:
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```
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pip install codeswitch
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```
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## Identify Language
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* Method-1
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```py
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-nepeng-lid-lince")
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model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-nepeng-lid-lince")
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lid_model = pipeline('ner', model=model, tokenizer=tokenizer)
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lid_model("put any nepali english code-mixed sentence")
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```
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* Method-2
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```py
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from codeswitch.codeswitch import LanguageIdentification
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lid = LanguageIdentification('nep-eng')
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text = "" # your code-mixed sentence
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result = lid.identify(text)
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print(result)
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```
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# codeswitch-spaeng-lid-lince
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This is a pretrained model for **language identification** of `spanish-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
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## Identify Language
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* Method-1
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---
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language:
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- es
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- en
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---
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# codeswitch-spaeng-ner-lince
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This is a pretrained model for **Name Entity Recognition** of `spanish-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
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This model is trained for this below repository.
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[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
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To install codeswitch:
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```
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pip install codeswitch
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```
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## Identify Language
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* Method-1
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```py
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-ner-lince")
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model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-spaeng-ner-lince")
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ner_model = pipeline('ner', model=model, tokenizer=tokenizer)
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ner_model("put any spanish english code-mixed sentence")
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```
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* Method-2
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```py
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from codeswitch.codeswitch import NER
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ner = NER('spa-eng')
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text = "" # your mixed sentence
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result = ner.tag(text)
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print(result)
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```
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@ -0,0 +1,45 @@
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---
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language:
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- es
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- en
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---
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# codeswitch-spaeng-pos-lince
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This is a pretrained model for **Part of Speech Tagging** of `spanish-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
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This model is trained for this below repository.
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[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
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To install codeswitch:
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```
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pip install codeswitch
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```
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## Identify Language
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* Method-1
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```py
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-pos-lince")
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model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-spaeng-pos-lince")
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pos_model = pipeline('ner', model=model, tokenizer=tokenizer)
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pos_model("put any spanish english code-mixed sentence")
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```
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* Method-2
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```py
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from codeswitch.codeswitch import POS
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pos = POS('spa-eng')
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text = "" # your mixed sentence
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result = pos.tag(text)
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print(result)
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```
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