easytorch VS FARM

Compare easytorch vs FARM and see what are their differences.

easytorch

EasyTorch is a research-oriented pytorch prototyping framework with a straightforward learning curve. It is highly robust and contains almost everything needed to perform any state-of-the-art experiments. (by sraashis)

FARM

:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering. (by deepset-ai)
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easytorch FARM
1 3
27 1,724
- 0.3%
6.3 0.0
5 months ago 5 months ago
Python Python
MIT License Apache License 2.0
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.

easytorch

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

FARM

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

What are some alternatives?

When comparing easytorch and FARM you can also consider the following projects:

image-quality-assessment - Convolutional Neural Networks to predict the aesthetic and technical quality of images.

Giveme5W1H - Extraction of the journalistic five W and one H questions (5W1H) from news articles: who did what, when, where, why, and how?

image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

Youtube-Code-Repository - Repository for most of the code from my YouTube channel

Questgen.ai - Question generation using state-of-the-art Natural Language Processing algorithms

haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.

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

tldr-transformers - The "tl;dr" on a few notable transformer papers (pre-2022).

BERTweet - BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)

lora - Using Low-rank adaptation to quickly fine-tune diffusion models.