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Falcon 40B Instruct 8bit by ichitaka

 »  All LLMs  »  ichitaka  »  Falcon 40B Instruct 8bit   URL Share it on

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  Arxiv:1911.02150   Arxiv:2005.14165   Arxiv:2104.09864   Arxiv:2205.14135   8-bit   8bit   Autotrain compatible   Custom code Dataset:tiiuae/falcon-refinedw...   En   Instruct   Pytorch   Quantized   Refinedweb   Region:us   Sharded

Falcon 40B Instruct 8bit Benchmarks

LLME Score: 0.11747
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Falcon 40B Instruct 8bit Parameters and Internals

Model Type
Causal decoder-only
Use Cases
Areas:
Chatbots, Instruction-following systems
Primary Use Cases:
Ready-to-use chat/instruct model based on Falcon-40B
Limitations:
Mostly trained on English data, may not generalize to other languages
Considerations:Ensure appropriate guardrails are in place for production systems.
Additional NotesThis model is a 40B parameter instruction model designed for use with GPUs using bitsandbytes for quantization.
Supported Languages
English (primary), French (secondary)
Training Details
Data Sources:
Baize, RefinedWeb
Data Volume:150M tokens
Methodology:Finetuned on a mixture of data
Context Length:2048
Hardware Used:
64 A100 40GB GPUs
Model Architecture:Causal decoder-only model with rotary positional embeddings and FlashAttention, multiquery attention, optimized MLP layer with single layer norm, parallel attention/MLP.
Safety Evaluation
Risk Categories:
Bias - related to language; stereotypes from online data
Ethical Considerations:Users should implement guardrails and assess risks for production use.
Responsible Ai Considerations
Fairness:Model primarily trained on English data, which may introduce bias and stereotypes.
Mitigation Strategies:Developers should consider precautions for production deployment.
Input Output
Accepted Modalities:
text
Performance Tips:Recommended for use on systems with adequate GPU resources.
LLM NameFalcon 40B Instruct 8bit
Repository 🤗https://huggingface.co/ichitaka/falcon-40b-instruct-8bit 
Base Model(s)  Medfalcon 40B Lora   nmitchko/medfalcon-40b-lora
Model Size40b
Required VRAM41.8 GB
Updated2024-11-12
Maintainerichitaka
Model TypeRefinedWeb
Instruction-BasedYes
Model Files  10.0 GB: 1-of-5   9.8 GB: 2-of-5   9.9 GB: 3-of-5   9.8 GB: 4-of-5   2.3 GB: 5-of-5
Supported Languagesen
Quantization Type8bit
Model ArchitectureRWForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.30.0.dev0
Is Biased0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size65024
Torch Data Typefloat16
Falcon 40B Instruct 8bit (ichitaka/falcon-40b-instruct-8bit)

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Note: green Score (e.g. "73.2") means that the model is better than ichitaka/falcon-40b-instruct-8bit.

Rank the Falcon 40B Instruct 8bit 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 v20241110
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