Instructor Embedding
xlang-ai
[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings
OPENAGENTSKILL / DIRECTORY
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Results: 15
xlang-ai
[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings
Blaizzy
MLX-Embeddings is the best package for running Vision and Language Embedding models locally on your Mac using MLX.
veniceai
Call POST /embeddings on Venice. Covers request shape (input, model, encoding_format, dimensions, user), OpenAI compatibility, response compression (gzip/br), and practi…
embeddings-benchmark
MTEB: Massive Text Embedding Benchmark
plasticityai
A fast, efficient universal vector embedding utility package.
qdrant
Fast, Accurate, Lightweight Python library to make State of the Art Embedding
TIGER-AI-Lab
This repo contains the code for "VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks" [ICLR 2025]
gaoisbest
word2vec, sentence2vec, machine reading comprehension, dialog system, text classification, pretrained language model (i.e., XLNet, BERT, ELMo, GPT), sequence labeling, i…
gorse-io
AI powered open source recommender system engine supports classical/LLM rankers and multimodal content via embedding
ARahim3
Fine-tune LLMs on your Mac with Apple Silicon. SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR fine-tuning — natively on MLX. Unsloth-compatible API.
NovaSearch-Team
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
topoteretes
Use when the user wants to connect cognee to external services — switching LLM or embedding providers (OpenAI, Azure, Gemini, Anthropic, Ollama, OpenRouter), changing da…
itsmostafa
AWS Bedrock foundation models for generative AI. Use when invoking foundation models, building AI applications, creating embeddings, configuring model access, or impleme…
taishi-i
Search all Japanese NLP resources (libraries, models, datasets, tutorials, dictionaries, Hugging Face). Accepts keywords or natural language questions in any language. U…
giuseppe-trisciuoglio
Implements document chunking, embedding generation, vector storage, and retrieval pipelines for Retrieval-Augmented Generation systems. Use when building RAG application…