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Is R efficient for sentiment analysis?
I would like to explore more about sentiment analysis but I cannot decide if I should start a project in python or R. What would you suggest?
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Tools that can combine a csv with meta data and feed them to LLM to query them
I have a table that looks like this: pd.DataFrame({'HRHHID': [1,2,3,4,5], 'HEHOUSUT': [2,3,1,4,2], 'HETELHHD': [1,2,1,1,1]}) I also have a txt file with some "meta data" for this file that ...
- 4,388
Using medspaCy with target rules from Metathesaurus
Before I start this discussion, here are some useful links that could provide some context: https://github.com/medspacy/medspacy https://www.nlm.nih.gov/research/umls/knowledge_sources/metathesaurus/...
- 113
An fantastic idea about using several sentences to represent another sentence in NLP
When learning NLP, I found that the current representation methods are basically word representation, so I wonder if there is a sentence representation? My hypothesis: to represent sentences using ...
- 15.9k
What are the advantages and disadvantages of using spaCy vs. NLTK for NLP tasks?
I am currently working on several NLP projects and I'm trying to decide between using spaCy and NLTK as my main NLP library. Both libraries seem to offer a range of features, but I'm not sure which ...
- 115
Classifier-Free-Guidance with Transformers
I'm working on music generation using transformers. Using the decoder part for the audio tokens with text conditioning by the T5 encoder In Classifier-Free-Guidance, the text conditioning randomly ...
- 59
Post-Processing Arabic OCR
Has anyone worked in a place where they extract a lot of text using Arabic OCR and then clean it to be as accurate as possible? How is this done? For example, if you digitize many documents and use ...
- 1
How are OCR texts post-processed to increase accuracy of recognition?
Has anyone worked in a company where they extract large amounts of text using OCR and then clean the text to be as accurate as possible? How is this done? Say I digitize a lot of legal documents, run ...
- 1
How to Develop an AI Model for Generating Website Templates from Text Prompts?
I am working on a project to develop an AI model that can generate website templates based on user-provided text prompts. The model should be able to interpret details such as desired features, color ...
Long Context Embedding Models eg. bge-m3 - To Chunk or Not to Chunk?
bge-m3 is highly performant embedding model that can encode both sparse and dense. It has a context length of 8kb. What I am wondering is with such models if it would be useful to BOTH long encode ...
- 11
Am I overengineering my lenient NER F1 measures
Hi, all I need to customize my F1 measurement a lot when evaluating my fine-tuned NER model performance. But I don't see other people with similar issues. I wonder if I am doing the wrong thing, or if ...
- 152
What is your ideal development environment for deep learning/NLP?
I'm curious on what are the ideal development setups for NLP developers who train deep learning models? I know in my journey to work more with deep learning, I use Jupyter Notebooks a lot, but I'm ...
- 146
Can you help a classification algorithm by offering it cues?
Is there a way in which you can teach a classification algorithm to learn better from sparse data. I was also thinking about the possibility of giving it cues as a list of words or phrases. If you ...
LLM learning roadblock: how to fine-tune a model with zero budget
As an early learner in LLM I completed most of the hugging face tutorials without much trouble on a laptop. Once I move past that to wanting to fine tune a model with a large amount of data, my ...
- 301
Do you know more list of datasets with English sentences has idiom?
Do you know list of dataset with English sentences has idiom? I use it for research. I found these, but need more https://metatext.io/datasets/english-possible-idiomatic-expressions-(epie) https://...
- 50.7k
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