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Latxa 7B Instruct by xezpeleta

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Base model:adapter:hitz/latxa-...   Base model:hitz/latxa-7b-v1   Chat   Dataset:xezpeleta/oasst2 eu   Endpoints compatible   Eu   Gguf   Instruct   Latxa   Llama   Peft   Quantized   Region:us   Safetensors   Sft   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/xezpeleta/latxa-7b-instruct 

Latxa 7B Instruct Benchmarks

LLME Score: 0.14584
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Latxa 7B Instruct Parameters and Internals

Model Type 
text-generation
Supported Languages 
eu (Basque)
Training Details 
Data Sources:
xezpeleta/oasst2_eu
Methodology:
Instruction fine-tuning using OASST2 dataset, translated to Basque using Helsinki-NLP Opus MT
LLM NameLatxa 7B Instruct
Repository 🤗https://huggingface.co/xezpeleta/latxa-7b-instruct 
Base Model(s)  Latxa 7B V1   HiTZ/latxa-7b-v1
Model Size7b
Required VRAM13.5 GB
Updated2025-06-09
Maintainerxezpeleta
Model Typellama
Instruction-BasedYes
Model Files  13.5 GB   4.9 GB: 1-of-3   5.0 GB: 2-of-3   3.6 GB: 3-of-3
Supported Languageseu
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureLlamaForCausalLM
Context Length4096
Model Max Length4096
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16
Latxa 7B Instruct (xezpeleta/latxa-7b-instruct)

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Note: green Score (e.g. "73.2") means that the model is better than xezpeleta/latxa-7b-instruct.

Rank the Latxa 7B Instruct Capabilities

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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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Release v20241124
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