Flair

| | `[SEP]` | 93.76 +- 0.13 |

Breaking Changes

Reorganized package structure 12

There are now two packages: `flair.models` and `flair.trainers` for the models and model trainers respectively.

Models package
`flair.models` contains 3 model classes: `SequenceTagger`, `TextClassifier` and `LanguageModel`.

Trainers package
`flair.trainers` contains 3 model trainer classes: `SequenceTaggerTrainer`, `TextClassifierTrainer` and `LanguageModelTrainer`.

Direct import from package
You call these classes directly from the packages, for instance the SequenceTagger is now instantiated as:

python
from flair.models import SequenceTagger
tagger = SequenceTagger.load('ner')


Reorganized embeddings 12

Clear distinction between token-level and document-level embeddings by adding two classes, namely `TokenEmbeddings` and `DocumentEmbeddings` from which respective embeddings need to inherit.


New Features

LanguageModelTrainer 24 17

Added `LanguageModelTrainer` class to train your own LM embeddings.

Document Classification 10

Added experimental `TextClassifier` model for document-level text classification. Also added corresponding model trainer class, i.e. `TextClassifierTrainer`.

Batch prediction 7

Added batching into prediction method for faster sequence tagging

CPU-friendly pre-trained models 29

Added pre-trained models with smaller LM embeddings for faster CPU-inference speed

You can load them by adding '-fast' to the model name. Only for English at present.
python
from flair.models import SequenceTagger
tagger = SequenceTagger.load('ner-fast')


Learning Rate Scheduling 19

Added learning rate schedulers to all trainer classes for improved learning rate annealing functionality and control.

Auto-spawn on GPUs 19

All model classes now automatically spawn on GPUs if available. The separate `.cuda()` call is no longer necessary.

Bug Fixes

Retagging error 23

Fixed error that occurred when using multiple pre-trained taggers on the same sentence.

Empty sentence error 33

Fixed error that caused data fetchers to sometimes create empty sentences.

Other

Unit Tests 15

Added a large set of automated unit tests for better stability.

Documentation 15

Expanded documentation and tutorials. Also expanded descriptions of APIs.

Code Simplifications in sequence tagger 19

A number of code simplifications all around, hopefully making the code easier to understand.

First release of Flair Framework

Static word embeddings:
- includes prepared word embeddings from GloVe, FastText, Numberbatch and Extvec
- includes prepared word embeddings for English, German and Swedish

Contextual string embeddings:
- includes pre-trained models for English and German

Text embeddings:
- Two experimental methods for full-text embeddings (LSTM and Mean)

Sequence labeling:
- pre-trained models for English (PoS-tagging, chunking and NER)
- pre-trained models for German (PoS-tagging and NER)
- experimental semantic frame detector for English