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OLMo 1B Instruct Alpaca Amc by amc-madalin

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OLMo 1B Instruct Alpaca Amc is an open-source language model by amc-madalin. Features: 1b LLM, VRAM: 2.4GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.12.

  Custom code   Dataset:vicgalle/alpaca-gpt4   En   Instruct   Olmo   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/amc-madalin/OLMo-1B-instruct-alpaca_amc 

OLMo 1B Instruct Alpaca Amc Benchmarks

LLME Score: 0.11789
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OLMo 1B Instruct Alpaca Amc (amc-madalin/OLMo-1B-instruct-alpaca_amc)
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OLMo 1B Instruct Alpaca Amc Parameters and Internals

Model Type 
Transformer-based autoregressive language model
Use Cases 
Areas:
research and experimentation with Open LLMs
Applications:
Conversational agents, Interactive storytelling, Educational tool
Limitations:
biases present in its training data
Considerations:
Users should be aware of these potential biases and limitations.
Additional Notes 
Model fine-tuned specifically for interactive chatting applications
Supported Languages 
en (proficient)
Training Details 
Data Sources:
vicgalle/alpaca-gpt4
Data Volume:
52K instruction-following demonstrations
Methodology:
fine-tuning
Context Length:
512
Model Architecture:
Transformer-based
Input Output 
Input Format:
Conversational prompts
Accepted Modalities:
text
Output Format:
Text response
Performance Tips:
Fine-tuned for chatting, ensure input format aligns with expectations
LLM NameOLMo 1B Instruct Alpaca Amc
Repository 🤗https://huggingface.co/amc-madalin/OLMo-1B-instruct-alpaca_amc 
Model Size1b
Required VRAM2.4 GB
Updated2025-12-07
Maintaineramc-madalin
Model Typeolmo
Instruction-BasedYes
Model Files  2.4 GB
Supported Languagesen
Model ArchitectureOLMoForCausalLM
Licenseapache-2.0
Transformers Version4.37.2
Tokenizer ClassOLMoTokenizer
Padding Token<|padding|>
Vocabulary Size50280
Torch Data Typebfloat16

Rank the OLMo 1B Instruct Alpaca Amc 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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