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Alpaca 13B by chavinlo

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Alpaca 13B is an open-source language model by chavinlo. Features: 13b LLM, VRAM: 52.1GB, LLM Explorer Score: 0.07.

  Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/chavinlo/alpaca-13b 

Alpaca 13B Benchmarks

LLME Score: 0.07314
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Alpaca 13B (chavinlo/alpaca-13b)
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Alpaca 13B Parameters and Internals

Model Type 
text generation, instruction-following
Use Cases 
Areas:
research, education
Applications:
instruction following tasks, text completion
Primary Use Cases:
Convert instructions to formal commands, Summarizing lengthy texts
Limitations:
May not reliably solve nuanced or ethical dilemmas, Should not be used for high-stakes decisions without human oversight
Considerations:
Ensure outputs are verified by a human for critical applications.
Additional Notes 
Developed without requiring the LoRA tuning strategy, enhancing deployment simplicity.
Training Details 
Data Sources:
OpenAI API, instruction-following datasets
Methodology:
Fine-tuning using instruction-following data
Context Length:
2048
Hardware Used:
NVIDIA A100 GPUs
Model Architecture:
Transformer
Safety Evaluation 
Methodologies:
red teaming, bias evaluations
Risk Categories:
bias, misinformation
Ethical Considerations:
Intended to reduce bias and ensure safe outputs
Responsible Ai Considerations 
Fairness:
The model aims to mitigate biases present in the data.
Transparency:
The model weights and code are openly available for audit.
Accountability:
Stanford University is accountable for developing and releasing the model.
Mitigation Strategies:
Continuous monitoring and updates to numerical thresholds and training datasets for fairness.
Input Output 
Input Format:
Text prompt following specific instruction formats
Accepted Modalities:
text
Output Format:
Text with actionable completion or responses
Performance Tips:
Tailor prompts to reduce ambiguity for coherent responses.
Release Notes 
Version:
0.1.0
Date:
2023-10-01
Notes:
Initial release without LoRA adaptation. Focuses on efficiency improvements.
LLM NameAlpaca 13B
Repository 🤗https://huggingface.co/chavinlo/alpaca-13b 
Model Size13b
Required VRAM52.1 GB
Updated2025-10-16
Maintainerchavinlo
Model Typellama
Model Files  10.0 GB: 1-of-6   9.9 GB: 2-of-6   9.9 GB: 3-of-6   9.9 GB: 4-of-6   9.9 GB: 5-of-6   2.5 GB: 6-of-6   0.0 GB
Model ArchitectureLLaMAForCausalLM
Model Max Length512
Transformers Version4.27.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32001
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than chavinlo/alpaca-13b.

Rank the Alpaca 13B 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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