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Setfit Alternatives
Similar projects and alternatives to setfit
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txtai
đź’ˇ All-in-one AI framework for semantic search, LLM orchestration and language model workflows
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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Graal
GraalVM compiles applications into native executables that start instantly, scale fast, and use fewer compute resources 🚀
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FLiPStackWeekly
FLaNK AI Weekly covering Apache NiFi, Apache Flink, Apache Kafka, Apache Spark, Apache Iceberg, Apache Ozone, Apache Pulsar, and more...
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motion-diffusion-model
The official PyTorch implementation of the paper "Human Motion Diffusion Model"
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SUPIR
SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.
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fastfit
FastFit ⚡ When LLMs are Unfit Use FastFit ⚡ Fast and Effective Text Classification with Many Classes
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CSL
[COLING 2022] CSL: A Large-scale Chinese Scientific Literature Dataset ä¸ć–‡ç§‘ĺ¦ć–‡çŚ®ć•°ćŤ®é›†
setfit discussion
setfit reviews and mentions
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🏎️ Faster, Cheaper, Better: The Power of Model Routing
Model routing offers tangible benefits—cost savings, faster responses, and efficient resource use—making it a valuable tool for businesses and developers. With the resources provided (dataset, code, and model), you can adapt this approach to your own use case. For further exploration, check out the SetFit documentation or experiment with different embedding models to suit your language needs.
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What Happened to Bert and T5?
Yes, no zero shot. Few shot is possible for some use cases with setfit: https://github.com/huggingface/setfit and the very recent Fastfit: https://github.com/IBM/fastfit ( https://arxiv.org/pdf/2404.12365 )
- FLaNK Stack 05 Feb 2024
- Smarter Summaries with Finetuning GPT-3.5 and Chain of Density
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[Discussion] Convince me that this training set contamination is fine (or not)
It did, sorry for the hasty edits! I removed that part b/c I realized that there isn't a compelling-enough reason for me to believe that text similarity is clearly inappropriate. In fact, you can train the Pr(condition | chat) classifier I suggested above using similarity training! Use SetFit for that. In the end you'll get a classifier and a similarity model.
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Ask HN: What's the best framework for text classification (few-shot learning)?
[3] https://github.com/huggingface/setfit
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Is it worth using LLMs like GPT-3 for text classification?
There's also kinda related approaches like SetFit which calculate embeddings from pretrained transformer models then then fit a classifier on top of the embeddings. I've yet to try it but it supposedly works well with very few labelled examples.
- LLMs for Text Classification (7B parameters)
- GPT-3 vs GPT-Neo / GPT-J for startup classification
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Ideas on how to improve classification and scoring using Mean Pooled Sentence Embeddings
You could have a look at setfit.
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A note from our sponsor - SaaSHub
www.saashub.com | 11 Aug 2026
Stats
huggingface/setfit is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of setfit is Jupyter Notebook.