added multiple model_cards for below models (#6666)

* Create README.md

* Update README.md

* Create README.md

* Update README.md

* added multiple codeswitch model

model_cards/sagorsarker/codeswitch-hineng-lid-lince/README.md

@@ -7,6 +7,7 @@ language:
 # codeswitch-hineng-lid-lince
 This is a pretrained model for **language identification** of `hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
 
+
 ## Identify Language
 
 * Method-1

model_cards/sagorsarker/codeswitch-hineng-ner-lince/README.md

+---
+language:
+- hi
+- en
+---
+
+# codeswitch-hineng-ner-lince
+This is a pretrained model for **Name Entity Recognition** of `Hindi-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
+
+This model is trained for this below repository. 
+
+[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
+
+To install codeswitch:
+
+```
+pip install codeswitch
+```
+
+## Identify Language
+
+* Method-1
+
+```py
+
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince")
+
+model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-hineng-ner-lince")
+
+ner_model = pipeline('ner', model=model, tokenizer=tokenizer)
+
+ner_model("put any hindi english code-mixed sentence")
+
+```
+
+* Method-2
+
+```py
+from codeswitch.codeswitch import NER
+ner = NER('hin-eng')
+text = "" # your mixed sentence 
+result = ner.tag(text)
+print(result)
+
+```

model_cards/sagorsarker/codeswitch-hineng-pos-lince/README.md

+---
+language:
+- hi
+- en
+---
+
+# codeswitch-hineng-pos-lince
+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)
+
+This model is trained for this below repository. 
+
+[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
+
+To install codeswitch:
+
+```
+pip install codeswitch
+```
+
+## Identify Language
+
+* Method-1
+
+```py
+
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-hineng-pos-lince")
+
+model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-hineng-pos-lince")
+pos_model = pipeline('ner', model=model, tokenizer=tokenizer)
+
+pos_model("put any hindi english code-mixed sentence")
+
+```
+
+* Method-2
+
+```py
+from codeswitch.codeswitch import POS
+pos = POS('hin-eng')
+text = "" # your mixed sentence 
+result = pos.tag(text)
+print(result)
+```

model_cards/sagorsarker/codeswitch-nepeng-lid-lince/README.md

+---
+language:
+- ne
+- en
+---
+
+# codeswitch-nepeng-lid-lince
+This is a pretrained model for **language identification** of `nepali-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home).
+
+This model is trained for this below repository. 
+
+[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
+
+To install codeswitch:
+
+```
+pip install codeswitch
+```
+
+## Identify Language
+
+* Method-1
+
+```py
+
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-nepeng-lid-lince")
+
+model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-nepeng-lid-lince")
+lid_model = pipeline('ner', model=model, tokenizer=tokenizer)
+
+lid_model("put any nepali english code-mixed sentence")
+
+```
+
+* Method-2
+
+```py
+from codeswitch.codeswitch import LanguageIdentification
+lid = LanguageIdentification('nep-eng') 
+text = "" # your code-mixed sentence 
+result = lid.identify(text)
+print(result)
+
+```
+

model_cards/sagorsarker/codeswitch-spaeng-lid-lince/README.md

@@ -7,6 +7,7 @@ language:
 # codeswitch-spaeng-lid-lince
 This is a pretrained model for **language identification** of `spanish-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
 
+
 ## Identify Language
 
 * Method-1

model_cards/sagorsarker/codeswitch-spaeng-ner-lince/README.md

+---
+language:
+- es
+- en
+---
+
+# codeswitch-spaeng-ner-lince
+This is a pretrained model for **Name Entity Recognition** of `spanish-english` code-mixed data used from [LinCE](https://ritual.uh.edu/lince/home)
+
+This model is trained for this below repository. 
+
+[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
+
+To install codeswitch:
+
+```
+pip install codeswitch
+```
+
+## Identify Language
+
+* Method-1
+
+```py
+
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-ner-lince")
+
+model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-spaeng-ner-lince")
+
+ner_model = pipeline('ner', model=model, tokenizer=tokenizer)
+
+ner_model("put any spanish english code-mixed sentence")
+
+```
+
+* Method-2
+
+```py
+from codeswitch.codeswitch import NER
+ner = NER('spa-eng')
+text = "" # your mixed sentence 
+result = ner.tag(text)
+print(result)
+```

model_cards/sagorsarker/codeswitch-spaeng-pos-lince/README.md

+---
+language:
+- es
+- en
+---
+
+# codeswitch-spaeng-pos-lince
+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)
+
+This model is trained for this below repository. 
+
+[https://github.com/sagorbrur/codeswitch](https://github.com/sagorbrur/codeswitch)
+
+To install codeswitch:
+
+```
+pip install codeswitch
+```
+
+## Identify Language
+
+* Method-1
+
+```py
+
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+
+tokenizer = AutoTokenizer.from_pretrained("sagorsarker/codeswitch-spaeng-pos-lince")
+
+model = AutoModelForTokenClassification.from_pretrained("sagorsarker/codeswitch-spaeng-pos-lince")
+pos_model = pipeline('ner', model=model, tokenizer=tokenizer)
+
+pos_model("put any spanish english code-mixed sentence")
+
+```
+
+* Method-2
+
+```py
+from codeswitch.codeswitch import POS
+pos = POS('spa-eng')
+text = "" # your mixed sentence 
+result = pos.tag(text)
+print(result)
+```