adaptnlp VS Deep-Learning-Experiments

Compare adaptnlp vs Deep-Learning-Experiments and see what are their differences.

adaptnlp

An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models. (by Novetta)
NLP Pytorch Transformers Natural Language Processing Machine Learning Deep Learning deep-learning-tutorial Docker fine-tuning language-models Easy api-rest Bert Gpt Xlnet GPU ulmfit
Source Code
novetta.github.io
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Deep-Learning-Experiments

Videos, notes and experiments to understand deep learning (by roatienza)
Deep Learning deep-learning-tutorial Artificial intelligence Pytorch Vision Speech NLP
Source Code
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adaptnlp Deep-Learning-Experiments
2 1
414 1,081
0.0% -
0.0 8.3
over 2 years ago about 1 month ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 MIT License
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adaptnlp

Posts with mentions or reviews of adaptnlp. We have used some of these posts to build our list of alternatives and similar projects.

Deep-Learning-Experiments

Posts with mentions or reviews of Deep-Learning-Experiments. We have used some of these posts to build our list of alternatives and similar projects.
  • EEE 197 - Deep Learning
    1 project | /r/peyups | 25 Aug 2022
    Hello, took the course last sem. Maraming napa-drop sa amin dahil sa difficulty nung assignments pero doable naman. Open-source mismo yung course, available sya sa GitHub: https://github.com/roatienza/Deep-Learning-Experiments

What are some alternatives?

When comparing adaptnlp and Deep-Learning-Experiments you can also consider the following projects:

Basic-UI-for-GPT-J-6B-with-low-vram - A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.

conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

keytotext - Keywords to Sentences

DeepLearning - Contains all my works, references for deep learning

fastai - The fastai deep learning library

python_autocomplete - Use Transformers and LSTMs to learn Python source code

gector - Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)

nn - 🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

browser-ml-inference - Edge Inference in Browser with Transformer NLP model

pytorch-deepdream - PyTorch implementation of DeepDream algorithm (Mordvintsev et al.). Additionally I've included playground.py to help you better understand basic concepts behind the algo.

Transformers-Tutorials - This repository contains demos I made with the Transformers library by HuggingFace.

TTS - :robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)

adaptnlp vs Basic-UI-for-GPT-J-6B-with-low-vram Deep-Learning-Experiments vs conformal_classification adaptnlp vs keytotext Deep-Learning-Experiments vs DeepLearning adaptnlp vs fastai Deep-Learning-Experiments vs python_autocomplete adaptnlp vs gector Deep-Learning-Experiments vs nn adaptnlp vs browser-ml-inference Deep-Learning-Experiments vs pytorch-deepdream adaptnlp vs Transformers-Tutorials Deep-Learning-Experiments vs TTS