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Candle TinyLlama 1.1B Chat V1.0 by DanielClough

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Candle TinyLlama 1.1B Chat V1.0 is an open-source language model by DanielClough. Features: 1.1b LLM, VRAM: 2.2GB, Context: 2K, License: apache-2.0, Quantized, LLM Explorer Score: 0.16, Arc: 36.6, HellaSwag: 61.7, MMLU: 25.8, GSM8K: 2.1.

Dataset:tinyllama/tinyllama-1....   En   Endpoints compatible   Gguf   Llama   Q4   Quantized   Region:us   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/DanielClough/Candle_TinyLlama-1.1B-Chat-v1.0 

Candle TinyLlama 1.1B Chat V1.0 Benchmarks

ARC: 36.6 vs 96.7 (so35)-62.2%
HellaSwag: 61.66 vs 95.3 (gpt4)-35.3%
MMLU: 25.78 vs 88.3 (so35)-70.8%
GSM8K: 2.12 vs 96.4 (so35)-97.8%
LLME Score: 0.15511
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Candle TinyLlama 1.1B Chat V1.0 (DanielClough/Candle_TinyLlama-1.1B-Chat-v1.0)
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Candle TinyLlama 1.1B Chat V1.0 Parameters and Internals

Model Type 
text-generation
Additional Notes 
This repo includes `.gguf` built for HuggingFace/Candle. Note: They will not work with `llama.cpp`.
Supported Languages 
language_en (proficient)
LLM NameCandle TinyLlama 1.1B Chat V1.0
Repository 🤗https://huggingface.co/DanielClough/Candle_TinyLlama-1.1B-Chat-v1.0 
Base Model(s)  Sft Tiny Chatbot   snshrivas10/sft-tiny-chatbot
Model Size1.1b
Required VRAM2.2 GB
Updated2026-05-09
MaintainerDanielClough
Model Typellama
Model Files  2.2 GB   0.4 GB   0.5 GB   0.6 GB   0.7 GB   0.6 GB   0.8 GB   0.8 GB   0.8 GB   0.9 GB   1.2 GB   1.2 GB   1.3 GB   2.2 GB: 1-of-1
Supported Languagesen
GGUF QuantizationYes
Quantization Typeq4|gguf
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.35.0
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than DanielClough/Candle_TinyLlama-1.1B-Chat-v1.0.

Rank the Candle TinyLlama 1.1B Chat V1.0 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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