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Falcon 40B Instruct GPTQ Inference Endpoints by philschmid

 »  All LLMs  »  philschmid  »  Falcon 40B Instruct GPTQ Inference Endpoints   URL Share it on

  15   
  Arxiv:1911.02150   Arxiv:2005.14165   Arxiv:2104.09864   Arxiv:2205.14135   4bit   Autotrain compatible   Custom code Dataset:tiiuae/falcon-refinedw...   En   Endpoints compatible   Gptq   Instruct   Quantized   Refinedweb   Region:us
Model Card on HF 🤗: https://huggingface.co/philschmid/falcon-40b-instruct-GPTQ-inference-endpoints 

Falcon 40B Instruct GPTQ Inference Endpoints Benchmarks

LLME Score: 0.09046
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 GPTQ Inference Endpoints (philschmid/falcon-40b-instruct-GPTQ-inference-endpoints)
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Falcon 40B Instruct GPTQ Inference Endpoints Parameters and Internals

Model Type 
Causal decoder-only
Use Cases 
Areas:
Chatbots, Instruction-based tasks
Primary Use Cases:
Chat datasets
Limitations:
Limited generalization to non-English languages
Considerations:
Guardrails recommended for production use
Additional Notes 
Experimental GPTQ model; support is limited.
Supported Languages 
English (primarily trained), French (also supported)
Training Details 
Data Sources:
Baize, RefinedWeb
Data Volume:
150M tokens
Methodology:
finetuned
Context Length:
2048
Hardware Used:
64 A100 40GB GPUs
Model Architecture:
Adapted from GPT-3, causal decoder-only with rotary positional embeddings and FlashAttention
Input Output 
Accepted Modalities:
text
Performance Tips:
Expected to be slow with around 0.7 tokens/s
LLM NameFalcon 40B Instruct GPTQ Inference Endpoints
Repository 🤗https://huggingface.co/philschmid/falcon-40b-instruct-GPTQ-inference-endpoints 
Model Size40b
Required VRAM22.5 GB
Updated2025-08-21
Maintainerphilschmid
Model TypeRefinedWeb
Instruction-BasedYes
Model Files  22.5 GB
Supported Languagesen
GPTQ QuantizationYes
Quantization Typegptq|4bit
Model ArchitectureRWForCausalLM
Licenseapache-2.0
Model Max Length2048
Transformers Version4.29.2
Is Biased0
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size65024
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than philschmid/falcon-40b-instruct-GPTQ-inference-endpoints.

Rank the Falcon 40B Instruct GPTQ Inference Endpoints 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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