CAMEL 33B Combined Data SuperHOT 8K GPTQ by TheBloke

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  4-bit   Autotrain compatible   Custom code   Ext 8k   Gptq   Llama   Quantized   Region:us   Safetensors

CAMEL 33B Combined Data SuperHOT 8K GPTQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CAMEL 33B Combined Data SuperHOT 8K GPTQ (TheBloke/CAMEL-33B-Combined-Data-SuperHOT-8K-GPTQ)

CAMEL 33B Combined Data SuperHOT 8K GPTQ Parameters and Internals

Model Type 
text generation
Additional Notes 
This is an experimental new GPTQ offering up to 8K context size, requires AutoGPTQ with trust_remote_code=True for Python code usage.
Training Details 
Data Sources:
CAMEL framework, ShareGPT, Alpaca dataset
Data Volume:
229K conversations
Methodology:
Finetuning
Context Length:
8192
Model Architecture:
GPTQ-for-LLaMa
Input Output 
Accepted Modalities:
text
Performance Tips:
Ensure use of ExLlama for full 8K context; otherwise, 4K context can be used.
LLM NameCAMEL 33B Combined Data SuperHOT 8K GPTQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/CAMEL-33B-Combined-Data-SuperHOT-8K-GPTQ 
Model Size33b
Required VRAM18.1 GB
Updated2025-02-22
MaintainerTheBloke
Model Typellama
Model Files  18.1 GB
GPTQ QuantizationYes
Context Length8k
Quantization Typegptq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.30.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/CAMEL-33B-Combined-Data-SuperHOT-8K-GPTQ.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Data Analysis and Insight Generation  
Text Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227