Model by abanm

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  4bit   Autotrain compatible   Conversational   En   Endpoints compatible   Instruct   Llama   Quantized   Region:us   Safetensors   Sft   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF ๐Ÿค—: https://huggingface.co/abanm/model 

Model Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Model (abanm/model)

Model Parameters and Internals

LLM NameModel
Repository ๐Ÿค—https://huggingface.co/abanm/model 
Base Model(s)  unsloth/phi-3.5-mini-instruct-bnb-4bit   unsloth/phi-3.5-mini-instruct-bnb-4bit
Model Size3.8b
Required VRAM7.6 GB
Updated2025-01-21
Maintainerabanm
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.6 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.47.1
Tokenizer ClassLlamaTokenizer
Padding Token<|placeholder6|>
Vocabulary Size32064
Torch Data Typebfloat16

Best Alternatives to Model

Best Alternatives
Context / RAM
Downloads
Likes
Phi 3 5 Mini 3k Each128K / 7.6 GB60
Tara 3.8B146K / 7.6 GB930
Phi 3.5 Mini Instruct128K / 7.6 GB1665842
Phi 3 5 Mini Kp 12k Cfr Sft128K / 7.6 GB1310
Phi 3 5 Mini Tictactoe1200128K / 7.6 GB810
...3 Mini 128K Instruct LLaMAfied128K / 7.6 GB803
Llamaphi 3 128K Instruct128K / 7.6 GB821
...i 3 Mini 4K Instruct LLaMAfied4K / 7.6 GB24611
...nder Llamafied With 16bit GGUF4K / 7.6 GB220
Phillama 3.8B V0.14K / 7.6 GB8310
Note: green Score (e.g. "73.2") means that the model is better than abanm/model.

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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 v20241227