|
|
--- |
|
|
datasets: |
|
|
- sentence-transformers/msmarco |
|
|
--- |
|
|
# ⭐ [GLiClass](https://github.com/Knowledgator/GLiClass): Generalist and Lightweight Model for Sequence Classification |
|
|
|
|
|
This is an efficient zero-shot classifier inspired by [GLiNER](https://github.com/urchade/GLiNER/tree/main) work. It demonstrates the same performance as a cross-encoder while being more compute-efficient because classification is done at a single forward path. |
|
|
|
|
|
It can be used for `topic classification`, `sentiment analysis` and as a reranker in `RAG` pipelines. |
|
|
|
|
|
The model was trained on synthetic and licensed data that allow commercial use and can be used in commercial applications. |
|
|
|
|
|
This version of the model uses a layer-wise selection of features that enables a better understanding of different levels of language. The backbone model is [ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base), which effectively processes long sequences. |
|
|
|
|
|
### How to use: |
|
|
First of all, you need to install GLiClass library: |
|
|
```bash |
|
|
pip install gliclass |
|
|
pip install -U transformers>=4.48.0 |
|
|
``` |
|
|
|
|
|
Than you need to initialize a model and a pipeline: |
|
|
|
|
|
```python |
|
|
from gliclass import GLiClassModel, ZeroShotClassificationPipeline |
|
|
from transformers import AutoTokenizer |
|
|
|
|
|
model = GLiClassModel.from_pretrained("alexandrlukashov/gliclass_msmarco_merged") |
|
|
tokenizer = AutoTokenizer.from_pretrained("alexandrlukashov/gliclass_msmarco_merged", add_prefix_space=True) |
|
|
pipeline = ZeroShotClassificationPipeline(model, tokenizer, classification_type='multi-label', device='cuda:0') |
|
|
|
|
|
text = "I want to live in New York." |
|
|
labels =[ |
|
|
'York is a cathedral city in North Yorkshire, England, with Roman origins', |
|
|
'San Francisco,[23] officially the City and County of San Francisco, is a commercial, financial, and cultural center within Northern California, United States.', |
|
|
'New York, often called New York City (NYC),[b] is the most populous city in the United States', |
|
|
"New York City is the third album by electronica group Brazilian Girls, released in 2008.", |
|
|
"New York City was an American R&B vocal group.", |
|
|
"New York City is an album by the Peter Malick Group featuring Norah Jones.", |
|
|
"New York City: The Album is the debut studio album by American rapper Troy Ave. ", |
|
|
'"New York City" is a song by British new wave band The Armoury Show', |
|
|
] |
|
|
results = pipeline(text, labels, threshold=0.5)[0] #because we have one text |
|
|
for result in results: |
|
|
print(result["label"], "=>", result["score"]) |
|
|
``` |
|
|
|
|
|
### Benchmarking: |
|
|
| Dataset | Base NDCG@10 | GLiClass NDCG@10 | |
|
|
|---------|-------------|------------------| |
|
|
| NanoArguAna | 0.489 | 0.525 | |
|
|
| NanoClimateFEVER | 0.318 | 0.870 | |
|
|
| NanoDBPedia | 0.614 | 0.871 | |
|
|
| NanoFEVER | 0.809 | 0.770 | |
|
|
| NanoFiQA2018 | 0.437 | 0.719 | |
|
|
| NanoHotpotQA | 0.828 | 0.647 | |
|
|
| NanoMSMARCO | 0.540 | 0.445 | |
|
|
| NanoNFCorpus | 0.325 | 0.710 | |
|
|
| NanoNQ | 0.501 | 0.588 | |
|
|
| NanoQuoraRetrieval | 0.869 | 0.540 | |
|
|
| NanoSCIDOCS | 0.335 | 0.917 | |
|
|
| NanoSciFact | 0.710 | 0.652 | |
|
|
| NanoTouche2020 | 0.694 | 0.490 | |
|
|
| **NanoBEIR (mean)** | 0.574 | **0.673** | |