NLP-progress VS flair

Compare NLP-progress vs flair and see what are their differences.


Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks. (by sebastianruder)


A very simple framework for state-of-the-art Natural Language Processing (NLP) (by flairNLP)
Our great sponsors
  • Nanos - Run Linux Software Faster and Safer than Linux with Unikernels
  • Scout APM - A developer's best friend. Try free for 14-days
  • SaaSHub - Software Alternatives and Reviews
NLP-progress flair
14 6
19,419 10,994
- 1.7%
7.3 9.7
5 days ago 6 days ago
Python Python
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of NLP-progress. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-11.


Posts with mentions or reviews of flair. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-05.
  • How to create a dataset for training NER models when you only have entity data
    1 project | | 18 Oct 2021
    We have a list of entities in text files separated with a new line. We intend to train the flair model to detect these entities in text, but NER models require the entity to be labeled in a paragraph with BOI format.
  • Preparing data for training NER models
    1 project | | 11 Oct 2021
    Training most of the Named Entity Recognition (NER) models for example Flair usually needs to format data in BOI tagging) scheme as shown below where each sentence is separated by blank line
  • German POS Corpus for Commercial use
    2 projects | | 5 Oct 2021
    I had the same problem a couple years ago. I think Flair, form Zalando uses a different Corpus. However, it's not great and I am pretty sure they are infringing the license anyway...
  • Advice for how to approach classifying apartment posts on facebook?
    1 project | | 4 Jun 2021
    For example, my first approach to the pet sentences would be to label all sentences within a respective text corpus containing according information for either yes or no. You would then convert this to a tertiary tag set, something like ["pet allowed", "pet not allowed", "irrelevant"]. You could then try out a model based on SentenceBert, other sentence-level embeddings/language models or 1D CNNs for this. flairNLP ( is a small, little framework which provides comfortable high-level access to different common language models which integrates perfectly with pyTorch.
  • SpaCy VS Transformers for NER
    2 projects | | 11 Mar 2021
    For NER, if you don't need the full toolkit of spacy, I'd highly recommend checking out Flair. It will likely run faster than transformer-based models (like en_core_web_trf) and it tends to be one of the best performing approaches to NER.
  • [D] NLP Q: How to extract this part from a messy short text?
    1 project | | 4 Mar 2021
    You then train the whole thing on sequences where each position has a label that is begin/inside/outside and thus you can calculate cross-entropy loss. So all in all it is basically:, or any huggingface model "for sequence classificaiton" or but just char based instead of word based. The CRF layer (as included in flair) is optional but may be useful.

What are some alternatives?

When comparing NLP-progress and flair you can also consider the following projects:

Stanza - Official Stanford NLP Python Library for Many Human Languages

seqeval - A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

gensim - Topic Modelling for Humans

spacy-models - 💫 Models for the spaCy Natural Language Processing (NLP) library

MAX-Toxic-Comment-Classifier - Detect 6 types of toxicity in user comments.

nnsplit - Semantic text segmentation. For sentence boundary detection, compound splitting and more.

BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT