unilm
gensim
| unilm | gensim | |
|---|---|---|
| 40 | 18 | |
| 18,358 | 15,256 | |
| 1.7% | 0.9% | |
| 9.0 | 7.5 | |
| 9 days ago | 10 days ago | |
| Python | Python | |
| MIT License | GNU Lesser General Public License v3.0 only |
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.
unilm
- The Era of 1-Bit LLMs: Training_Tips, Code And_FAQ [pdf]
- The Era of 1-Bit LLMs: Training Tips, Code and FAQ
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The Era of 1-bit LLMs: ternary parameters for cost-effective computing
+1 On this, the real proof would have been testing both models side-by-side.
It seems that it may be published on GitHub [1] according to HuggingFace [2].
[1] https://github.com/microsoft/unilm/tree/master/bitnet
[2] https://huggingface.co/papers/2402.17764
- I'm an Old Fart and AI Makes Me Sad
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On building a semantic search engine
e5-mistral is essentially a distillation from gpt-4 to a smaller model. You can see here https://github.com/microsoft/unilm/blob/16da2f193b9c1dab0a69...
they actually have custom prompts for each dataset being tested.
Question would be, if you haven't seen the task before, what is a good prompt to prepend for your task?
IMO e5-mistral is overfit to MTEB
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Leveraging GPT-4 for PDF Data Extraction: A Comprehensive Guide
Layout LM v1, v2 and v3 models [ Github ] DocBERT [ Github ]
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Microsoft Publishes LongNet: Scaling Transformers to 1,000,000,000 Tokens
The repository is available here.
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Recommended open LLMs with image input modality?
It is missing kosmos-2. I remember its image captioning was(demo currently down) really good and it's almost as fast as llava and lavin.
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LongNet: Scaling Transformers to 1,000,000,000 Tokens
Should be this: https://github.com/microsoft/unilm/
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[R] LongNet: Scaling Transformers to 1,000,000,000 Tokens
This is from Microsoft Research (Asia). https://aka.ms/GeneralAI
gensim
- Aggregating news from different sources
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Understanding How Dynamic node2vec Works on Streaming Data
This is our optimization problem. Now, we hope that you have an idea of what our goal is. Luckily for us, this is already implemented in a Python module called gensim. Yes, these guys are brilliant in natural language processing and we will make use of it. 🤝
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Topic modeling --- allow multiple topics per statement
Try LDA as implemented in gemsin https://github.com/RaRe-Technologies/gensim
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Is it home bias or is data wrangling for machine learning in python much less intuitive and much more burdensome than in R?
Standout python NLP libraries include Spacy and Gensim, as well as pre-trained model availability in Hugginface. These libraries have widespread use in and support from industry and it shows. Spacy has best-in-class methods for pre-processing text for further applications. Gensim helps you manage your corpus of documents, and contains a lot of different tools for solving a common industry task, topic modeling.
- sentence transformer vector dimensionality reduction to 1
- Where to start for recommendation systems
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GET STARTED WITH TOPIC MODELLING USING GENSIM IN NLP
Here we have to install the gensim library in a jupyter notebook to be able to use it in our project, consider the code below;
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Show HN: I built a site that summarizes articles and PDFs using NLP
Nice work! I wonder if you're going the same challenges that gensim had for being generic in summarization.
For context:
> Despite its general-sounding name, the module will not satisfy the majority of use cases in production and is likely to waste people's time.
https://github.com/RaRe-Technologies/gensim/wiki/Migrating-f...
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[Research] Text summarization using Python, that can run on Android devices?
TextRank will work without any problems. https://radimrehurek.com/gensim/
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Topic modelling with Gensim and SpaCy on startup news
For the topic modelling itself, I am going to use Gensim library by Radim Rehurek, which is very developer friendly and easy to use.
What are some alternatives?
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
ERNIE - Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
scikit-learn - scikit-learn: machine learning in Python
involution - [CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
MLflow - Open source platform for the machine learning lifecycle
maelstrom - A workbench for writing toy implementations of distributed systems.
tensorflow - An Open Source Machine Learning Framework for Everyone
rasa - 💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Keras - Deep Learning for humans
memprompt - A method to fix GPT-3 after deployment with user feedback, without re-training.
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)