Deepset Xlm Roberta Large Squad2 4bits by RichardErkhov

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  4-bit   Autotrain compatible   Bitsandbytes   Endpoints compatible   Instruct   Region:us   Safetensors   Xlm-roberta

Deepset Xlm Roberta Large Squad2 4bits Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Deepset Xlm Roberta Large Squad2 4bits (RichardErkhov/deepset_-_xlm-roberta-large-squad2-4bits)
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Deepset Xlm Roberta Large Squad2 4bits Parameters and Internals

Model Type 
question-answering
Use Cases 
Areas:
research, commercial applications
Primary Use Cases:
extractive question answering
Limitations:
performance may vary across different languages
Supported Languages 
languages_supported (Multilingual), proficiency_levels (High)
Training Details 
Data Sources:
SQuAD 2.0
Methodology:
Extractive QA
Hardware Used:
4x Tesla v100
Model Architecture:
XLM-RoBERTa
Input Output 
Input Format:
questions and context documents
Accepted Modalities:
text
Output Format:
answers with scores
LLM NameDeepset Xlm Roberta Large Squad2 4bits
Repository ๐Ÿค—https://huggingface.co/RichardErkhov/deepset_-_xlm-roberta-large-squad2-4bits 
Model Size413.9m
Required VRAM0.7 GB
Updated2025-09-23
MaintainerRichardErkhov
Model Typexlm-roberta
Model Files  0.7 GB
Supported Languagesen
Model ArchitectureXLMRobertaForCausalLM
Licensecc-by-4.0
Context Length514
Model Max Length514
Transformers Version4.39.3
Tokenizer ClassXLMRobertaTokenizer
Padding Token<pad>
Vocabulary Size250002
Torch Data Typefloat16

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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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124