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NEPALIGPT 1.0 by Heem2

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  4-bit   4bit   Autotrain compatible Base model:quantized:unsloth/m... Base model:unsloth/mistral-7b-...   Bitsandbytes   En   Endpoints compatible   Mistral   Quantized   Region:us   Safetensors   Sft   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Heem2/NEPALIGPT-1.0 

NEPALIGPT 1.0 Benchmarks

LLME Score: 0.17413
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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NEPALIGPT 1.0 Parameters and Internals

Model Type 
text generation
Use Cases 
Primary Use Cases:
research, text generation
Supported Languages 
Nepali (primary)
Training Details 
Methodology:
Unsloth fine-tuning
Input Output 
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Use 4bit quantization to reduce memory usage
LLM NameNEPALIGPT 1.0
Repository 🤗https://huggingface.co/Heem2/NEPALIGPT-1.0 
Base Model(s)  Mistral 7B Bnb 4bit   unsloth/mistral-7b-bnb-4bit
Model Size7b
Required VRAM4.1 GB
Updated2025-06-09
MaintainerHeem2
Model Typemistral
Model Files  4.1 GB
Supported Languagesen
Quantization Type4bit
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16
NEPALIGPT 1.0 (Heem2/NEPALIGPT-1.0)

Best Alternatives to NEPALIGPT 1.0

Best Alternatives
Context / RAM
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...al Nemo Instruct 2407 Bnb 4bit128K / 8.3 GB25080727
...istral Nemo Base 2407 Bnb 4bit128K / 8.3 GB225417
...t 3.5 0106 128K 4.0bpw H6 EXL2128K / 3.9 GB221
...t 3.5 0106 128K 8.0bpw H8 EXL2128K / 7.4 GB191
...tral 7B Instruct V0.3 Bnb 4bit32K / 4.1 GB6309228
Mistral 7B V0.3 Bnb 4bit32K / 4.1 GB2434916
Mixtral V0.3 Full 16bit32K / 14.5 GB540
Mistral 7B Instruct V0.2 Fp1632K / 14.4 GB260
...tral 7B Instruct V0.2 Bnb 4bit32K / 4.1 GB2736132
Mistral 7B Instruct V0.2 4bit32K / 4.3 GB2291
Note: green Score (e.g. "73.2") means that the model is better than Heem2/NEPALIGPT-1.0.

Rank the NEPALIGPT 1.0 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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