haystack VS scibert

Compare haystack vs scibert and see what are their differences.

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. (by deepset-ai)
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haystack scibert
54 2
13,633 1,402
5.8% 0.0%
9.9 0.0
1 day ago about 2 years ago
Python Python
Apache License 2.0 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.

haystack

Posts with mentions or reviews of haystack. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-07.

scibert

Posts with mentions or reviews of scibert. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-15.

What are some alternatives?

When comparing haystack and scibert you can also consider the following projects:

langchain - 🦜🔗 Build context-aware reasoning applications

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]

paperai - 📄 🤖 Semantic search and workflows for medical/scientific papers

gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

BERT-pytorch - Google AI 2018 BERT pytorch implementation

BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!

clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

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

jina - ☁️ Build multimodal AI applications with cloud-native stack

galai - Model API for GALACTICA