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Falcon Rw 1B Instruct Openorca by ericzzz

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Falcon Rw 1B Instruct Openorca is an open-source language model by ericzzz. Features: 1b LLM, VRAM: 2.6GB, Context: 2K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.15, Arc: 34.6, HellaSwag: 60.9, MMLU: 28.8, GSM8K: 3.4.

  Dataset:open-orca/slimorca   En   Falcon   Instruct   Model-index   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/ericzzz/falcon-rw-1b-instruct-openorca 

Falcon Rw 1B Instruct Openorca Benchmarks

ARC: 34.56 vs 96.7 (so35)-64.3%
HellaSwag: 60.93 vs 95.3 (gpt4)-36.1%
MMLU: 28.77 vs 88.3 (so35)-67.4%
GSM8K: 3.41 vs 96.4 (so35)-96.5%
LLME Score: 0.14954
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Falcon Rw 1B Instruct Openorca (ericzzz/falcon-rw-1b-instruct-openorca)
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Falcon Rw 1B Instruct Openorca Parameters and Internals

Model Type 
text generation
Use Cases 
Primary Use Cases:
instruction-tuned applications
Limitations:
Inaccurate or misleading information, Prone to hallucinations, Limited understanding of complex queries
Considerations:
Users should verify information obtained and be responsible for their interactions with the model.
Training Details 
Data Sources:
Open-Orca/SlimOrca
Methodology:
instruction tuning
Model Architecture:
causal decoder-only
Input Output 
Input Format:
Prompts using tags for system message and instruction.
Accepted Modalities:
text
Output Format:
Generated text following a structured prompt format.
LLM NameFalcon Rw 1B Instruct Openorca
Repository 🤗https://huggingface.co/ericzzz/falcon-rw-1b-instruct-openorca 
Model Size1b
Required VRAM2.6 GB
Updated2026-05-16
Maintainerericzzz
Model Typefalcon
Instruction-BasedYes
Model Files  2.6 GB
Supported Languagesen
Model ArchitectureFalconForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.35.2
Is Biased1
Tokenizer ClassGPT2Tokenizer
Vocabulary Size50304
Torch Data Typebfloat16

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Rank the Falcon Rw 1B Instruct Openorca 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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