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TinyLlama 1.1B Intermediate 1.5T PTBR Instruct V2 by cnmoro

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TinyLlama 1.1B Intermediate 1.5T PTBR Instruct V2 is an open-source language model by cnmoro. Features: 1.1b LLM, VRAM: 2.2GB, Context: 4K, License: mit, Instruction-Based, LLM Explorer Score: 0.1.

  Autotrain compatible   En   Endpoints compatible   Instruct   Llama   Pt   Pytorch   Region:us
Model Card on HF 🤗: https://huggingface.co/cnmoro/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v2 

TinyLlama 1.1B Intermediate 1.5T PTBR Instruct V2 Benchmarks

LLME Score: 0.10323
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyLlama 1.1B Intermediate 1.5T PTBR Instruct V2 (cnmoro/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v2)
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TinyLlama 1.1B Intermediate 1.5T PTBR Instruct V2 Parameters and Internals

Model Type 
text-generation
Additional Notes 
This version is a work in progress, with final version expected to be v3 or v4.
Supported Languages 
pt (Portuguese), en (English)
Training Details 
Data Sources:
Portuguese instruct dataset
Methodology:
using axolotl
Input Output 
Input Format:
f"Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Instruction:\n{instruction}\n\n### Response:\n"
LLM NameTinyLlama 1.1B Intermediate 1.5T PTBR Instruct V2
Repository 🤗https://huggingface.co/cnmoro/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v2 
Model Size1.1b
Required VRAM2.2 GB
Updated2024-11-18
Maintainercnmoro
Model Typellama
Instruction-BasedYes
Model Files  2.2 GB
Supported Languagespt en
Model ArchitectureLlamaForCausalLM
Licensemit
Context Length4096
Model Max Length4096
Transformers Version4.34.1
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than cnmoro/TinyLlama-1.1B-intermediate-1.5T-PTBR-Instruct-v2.

Rank the TinyLlama 1.1B Intermediate 1.5T PTBR Instruct V2 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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