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Stella En 1.5B V5 by dunzhang

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Stella En 1.5B V5 is an open-source language model by dunzhang. Features: 1.5b LLM, VRAM: 6.2GB, Context: 128K, License: mit, LLM Explorer Score: 0.25.

  Arxiv:2205.13147   Autotrain compatible   Custom code   Endpoints compatible   Model-index   Mteb   Pytorch   Qwen2   Region:us   Safetensors   Sentence-similarity   Sentence-transformers   Text-embeddings-inference
Model Card on HF 🤗: https://huggingface.co/dunzhang/stella_en_1.5B_v5 

Stella En 1.5B V5 Benchmarks

LLME Score: 0.25164
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Stella En 1.5B V5 (dunzhang/stella_en_1.5B_v5)
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Stella En 1.5B V5 Parameters and Internals

Model Type 
SentenceTransformer, Retrieval, Classification, STS, PairClassification, Clustering, Summarization
Additional Notes 
The model comes with a series of `2_Dense_{dims}` folders for versatile output dimensions with minor performance differences across them. It requires a prompt for the best results in specific tasks.
Training Details 
Methodology:
The models are trained based on `Alibaba-NLP/gte-large-en-v1.5` and `Alibaba-NLP/gte-Qwen2-1.5B-instruct` and use [MRL](https://arxiv.org/abs/2205.13147) methodology.
Context Length:
512
Input Output 
Input Format:
Given a web search query, retrieve relevant passages that answer the query: {query}
Output Format:
Vectors with specified dimension, capable of complex similarity and retrieval tasks.
Performance Tips:
Use 1024 dimensions for a balance between performance and computational cost.
LLM NameStella En 1.5B V5
Repository 🤗https://huggingface.co/dunzhang/stella_en_1.5B_v5 
Model Size1.5b
Required VRAM6.2 GB
Updated2025-01-23
Maintainerdunzhang
Model Typeqwen2
Model Files  6.2 GB   6.2 GB
Model ArchitectureQwen2ForCausalLM
Licensemit
Context Length131072
Model Max Length131072
Transformers Version4.42.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151646
Torch Data Typefloat32
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than dunzhang/stella_en_1.5B_v5.

Rank the Stella En 1.5B V5 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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