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Ct2fast Falcon 40B by michaelfeil

 »  All LLMs  »  michaelfeil  »  Ct2fast Falcon 40B   URL Share it on

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  Arxiv:1911.02150   Arxiv:2005.14165   Arxiv:2101.00027   Arxiv:2104.09864   Arxiv:2205.14135   Arxiv:2306.01116   Ctranslate2 Dataset:tiiuae/falcon-refinedw...   De   En   Es   Float16   Fr   Int8   Region:us
Model Card on HF 🤗: https://huggingface.co/michaelfeil/ct2fast-falcon-40b 

Ct2fast Falcon 40B Benchmarks

LLME Score: 0.09119
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Ct2fast Falcon 40B (michaelfeil/ct2fast-falcon-40b)
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Ct2fast Falcon 40B Parameters and Internals

Model Type 
Causal decoder-only
Use Cases 
Areas:
Research, Specialization, Finetuning
Applications:
Summarization, Text generation, Chatbot
Primary Use Cases:
Research on large language models, Foundation for further specialization
Limitations:
Not suitable for production use without risk assessment and mitigation, Trained mostly on a few languages
Considerations:
Finetuning is recommended for specific tasks.
Additional Notes 
Quantized version intended to be identical in licensing to the original huggingface model.
Supported Languages 
English (high proficiency), German (high proficiency), Spanish (high proficiency), French (high proficiency), Italian (limited capabilities), Portuguese (limited capabilities), Polish (limited capabilities), Dutch (limited capabilities), Romanian (limited capabilities), Czech (limited capabilities), Swedish (limited capabilities)
Training Details 
Data Sources:
RefinedWeb, Books, Conversations, Code, Technical
Data Volume:
1,000B tokens
Context Length:
2048
Training Time:
Two months
Hardware Used:
384 A100 40GB GPUs
Model Architecture:
Adapted from GPT-3 with rotary positionnal embeddings, multiquery and FlashAttention.
Responsible Ai Considerations 
Fairness:
Falcon-40B carries stereotypes and biases present on the web.
Transparency:
Details of datasets and methodology provided.
Accountability:
It is recommended to further finetune the model and implement guardrails for production use.
Mitigation Strategies:
Users are recommended to consider finetuning and appropriate precautions for production use.
Input Output 
Input Format:
Text input for prompts
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
Use PyTorch 2.0 for optimal functionality.
Release Notes 
Version:
Converted on 2023-06-16
Date:
2023-06-16
Notes:
Converted using ct2-transformers-converter with int8_float16 quantization for improved efficiency.
LLM NameCt2fast Falcon 40B
Repository 🤗https://huggingface.co/michaelfeil/ct2fast-falcon-40b 
Model Size40b
Required VRAM41.3 GB
Updated2025-08-21
Maintainermichaelfeil
Model Files  41.3 GB
Supported Languagesen de es fr
Model ArchitectureAutoModel
Licenseapache-2.0
Model Max Length2048
Tokenizer ClassPreTrainedTokenizerFast

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Note: green Score (e.g. "73.2") means that the model is better than michaelfeil/ct2fast-falcon-40b.

Rank the Ct2fast Falcon 40B 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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