---
title: genre-linking-blink
canonical_url: "https://www.modelscope.cn/models/facebook/genre-linking-blink"
md_url: "https://www.modelscope.cn/models/facebook/genre-linking-blink.md"
repository: facebook/genre-linking-blink
last_updated: 2025-05-20
pipeline_tag: text2text-generation
tasks:
  - text2text-generation
model_type:
  - bart
architectures:
  - BartForConditionalGeneration
library_name:
  - transformer
  - tensorflow
  - pytorch
frameworks:
  - pytorch
language:
  - en
inference_backends:
  - "deploy_task text/emb"
  - "vllm 0.9.2"
downloads: 344
stars: 0
tags:
  - retrieval
  - entity-retrieval
  - named-entity-disambiguation
  - entity-disambiguation
  - named-entity-linking
  - entity-linking
  - text2text-generation
---

# genre-linking-blink

> genre-linking-blink - facebook 在 ModelScope 开源的模型。The GENRE (Generative ENtity REtrieval) system as presented in Autoregressive Entity Retrieval implemented in pytorch.

facebook/genre-linking-blink 是 ModelScope 魔搭社区上的text2text-generation模型，可用 deploy_task text/emb、vllm 0.9.2 部署。

- **Repository**: facebook/genre-linking-blink
- **Tasks**: text2text-generation
- **Inference backends**: deploy_task text/emb, vllm 0.9.2
- **Tags**: retrieval, entity-retrieval, named-entity-disambiguation, entity-disambiguation, named-entity-linking, entity-linking, text2text-generation
- **Downloads**: 344
- **Stars**: 0
- **Last updated**: 2025-05-20

Source: https://www.modelscope.cn/models/facebook/genre-linking-blink

---

# GENRE


The GENRE (Generative ENtity REtrieval) system as presented in [Autoregressive Entity Retrieval](https://arxiv.org/abs/2010.00904) implemented in pytorch.

In a nutshell, GENRE uses a sequence-to-sequence approach to entity retrieval (e.g., linking), based on fine-tuned [BART](https://arxiv.org/abs/1910.13461) architecture. GENRE performs retrieval generating the unique entity name conditioned on the input text using constrained beam search to only generate valid identifiers. The model was first released in the [facebookresearch/GENRE](https://github.com/facebookresearch/GENRE) repository using `fairseq` (the `transformers` models are obtained with a conversion script similar to [this](https://github.com/huggingface/transformers/blob/master/src/transformers/models/bart/convert_bart_original_pytorch_checkpoint_to_pytorch.py).

This model was trained on the full training set of [BLINK](https://arxiv.org/abs/1911.03814) (i.e., 9M datapoints for entity-disambiguation grounded on Wikipedia).

## BibTeX entry and citation info

**Please consider citing our works if you use code from this repository.**

```bibtex
@inproceedings{decao2020autoregressive,
  title={Autoregressive Entity Retrieval},
  author={Nicola {De Cao} and Gautier Izacard and Sebastian Riedel and Fabio Petroni},
  booktitle={International Conference on Learning Representations},
  url={https://openreview.net/forum?id=5k8F6UU39V},
  year={2021}
}
```

## Usage

Here is an example of generation for Wikipedia page disambiguation:

```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

# OPTIONAL: load the prefix tree (trie), you need to additionally download
# https://huggingface.co/facebook/genre-linking-blink/blob/main/trie.py and 
# https://huggingface.co/facebook/genre-linking-blink/blob/main/kilt_titles_trie_dict.pkl
# import pickle
# from trie import Trie
# with open("kilt_titles_trie_dict.pkl", "rb") as f:
#     trie = Trie.load_from_dict(pickle.load(f))

tokenizer = AutoTokenizer.from_pretrained("facebook/genre-linking-blink")
model = AutoModelForSeq2SeqLM.from_pretrained("facebook/genre-linking-blink").eval()

sentences = ["Einstein was a [START_ENT] German [END_ENT] physicist."]

outputs = model.generate(
    **tokenizer(sentences, return_tensors="pt"),
    num_beams=5,
    num_return_sequences=5,
    # OPTIONAL: use constrained beam search
    # prefix_allowed_tokens_fn=lambda batch_id, sent: trie.get(sent.tolist()),
)

tokenizer.batch_decode(outputs, skip_special_tokens=True)
```
which outputs the following top-5 predictions (using constrained beam search)
```
['Germans',
 'Germany',
 'German Empire',
 'Weimar Republic',
 'Greeks']
```