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Nepali LLM by shivam9980

 »  All LLMs  »  shivam9980  »  Nepali LLM   URL Share it on

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  4bit   Autotrain compatible Base model:finetune:unsloth/ge... Base model:unsloth/gemma-2-9b-...   Dataset:uonlp/culturax   Endpoints compatible   Gemma2   Ne   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/shivam9980/Nepali-LLM 

Nepali LLM Benchmarks

LLME Score: 0.21837
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Nepali LLM (shivam9980/Nepali-LLM)

Nepali LLM Parameters and Internals

Model Type 
text-generation-inference, transformers
Additional Notes 
This gemma2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameNepali LLM
Repository 🤗https://huggingface.co/shivam9980/Nepali-LLM 
Base Model(s)  Gemma 2 9B Bnb 4bit   unsloth/gemma-2-9b-bnb-4bit
Model Size9b
Required VRAM20.5 GB
Updated2024-09-24
Maintainershivam9980
Model Typegemma2
Model Files  4.9 GB: 1-of-5   5.0 GB: 2-of-5   4.9 GB: 3-of-5   3.8 GB: 4-of-5   1.9 GB: 5-of-5
Supported Languagesne
Quantization Type4bit
Model ArchitectureGemma2ForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.44.2
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size271903
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than shivam9980/Nepali-LLM.

Rank the Nepali LLM 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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Release v20241227
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