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Alpaca Cerebras 6.7B by bjoernp

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  Arxiv:1910.09700   Dataset:tatsu-lab/alpaca   Dataset:yahma/alpaca-cleaned   En   Endpoints compatible   Lora   Region:us
Model Card on HF 🤗: https://huggingface.co/bjoernp/alpaca-cerebras-6.7B 

Alpaca Cerebras 6.7B Benchmarks

LLME Score: 0.07431
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Alpaca Cerebras 6.7B (bjoernp/alpaca-cerebras-6.7B)
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Alpaca Cerebras 6.7B Parameters and Internals

Model Type 
Transformer-based Language Model
Additional Notes 
Experiments used a private infrastructure with estimated total emissions of 0.97 kgCO2eq.
Supported Languages 
English (proficient)
Training Details 
Data Sources:
yhama/alpaca-cleaned, tatsu-lab/alpaca
Data Volume:
20 tokens per model parameter (Chinchilla scaling laws)
Methodology:
Pre-training and fine-tuning on Cerebras systems with LoRA adapter
Context Length:
2048
Hardware Used:
Andromeda AI supercomputer with 16 CS-2 wafer scale systems
Model Architecture:
GPT-3 style architecture with LoRA adapter
Input Output 
Input Format:
Byte Pair Encoding
Accepted Modalities:
text
Output Format:
Generated text
LLM NameAlpaca Cerebras 6.7B
Repository 🤗https://huggingface.co/bjoernp/alpaca-cerebras-6.7B 
Model Size6.7b
Required VRAM0 GB
Updated2025-10-08
Maintainerbjoernp
Model Files  0.0 GB
Supported Languagesen
Model ArchitectureAutoModel
Licenseapache-2.0
Is Biasednone
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesc_attn
LoRA Alpha16
LoRA Dropout0.05
R Param8

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Note: green Score (e.g. "73.2") means that the model is better than bjoernp/alpaca-cerebras-6.7B.

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Instruction Following and Task Automation  
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Release v20241124
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