---
license: mit
language:
- en
- fr
- de
- it
- es
- pt
- pl
- nl
- ru
pipeline_tag: token-classification
inference: false
tags:
- mBERT
- BERT
- generic
- entity-recognition
---

## Model

The [multilingual BERT](https://huggingface.co/bert-base-multilingual-cased) finetunned on an artificially annotated multilingual subset of [Oscar dataset](https://huggingface.co/datasets/oscar-corpus/OSCAR-2201). This model provides domain & language independent embedding for Entity Recognition Task.

## Usage

Embeddings can be used out of the box or fine-tuned on specific datasets. 

Get embeddings:

```python
import torch
import transformers


model = transformers.AutoModel.from_pretrained(
    'numind/entity-recognition-general-sota-v1',
    output_hidden_states=True,
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
    'numind/entity-recognition-general-sota-v1',
)

text = [
    "NuMind is an AI company based in Paris and USA.",
    "See other models from us on https://huggingface.co/numind"
]
encoded_input = tokenizer(
    text,
    return_tensors='pt',
    padding=True,
    truncation=True
)
output = model(**encoded_input)

# for better quality
emb = torch.cat(
    (output.hidden_states[-1], output.hidden_states[-7]),
    dim=2
)

# for better speed
# emb = output.hidden_states[-1]
```