
### Description
A Named Entity Recognition model trained on a customer feedback data using DistilBert.
Possible labels are:
- PRD: for certain products
- BRND: for brands

### Usage
```
from transformers import AutoTokenizer, AutoModelForTokenClassification
  
  tokenizer = AutoTokenizer.from_pretrained("CouchCat/ma_ner_v6_distil")
  
  model = AutoModelForTokenClassification.from_pretrained("CouchCat/ma_ner_v6_distil")
```
{"language": "en", "license": "mit", "tags": ["ner"], "widget": [{"text": "These shoes from Adidas fit quite well"}]}
transformers pytorch distilbert token-classification ner en license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #token-classification #ner #en #license-mit #autotrain_compatible #endpoints_compatible #region-us 


### Description
A Named Entity Recognition model trained on a customer feedback data using DistilBert.
Possible labels are:
- PRD: for certain products
- BRND: for brands

### Usage

### Description
A Named Entity Recognition model trained on a customer feedback data using DistilBert.
Possible labels are:
- PRD: for certain products
- BRND: for brands ### Usage
TAGS
#transformers #pytorch #distilbert #token-classification #ner #en #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Description
A Named Entity Recognition model trained on a customer feedback data using DistilBert.
Possible labels are:
- PRD: for certain products
- BRND: for brands ### Usage
passage: TAGS
#transformers #pytorch #distilbert #token-classification #ner #en #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Description
A Named Entity Recognition model trained on a customer feedback data using DistilBert.
Possible labels are:
- PRD: for certain products
- BRND: for brands### Usage