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Synthia 70B AWQ by TheBloke

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Synthia 70B AWQ is an open-source language model by TheBloke. Features: 70b LLM, VRAM: 36.6GB, Context: 2K, License: llama2, Quantized, LLM Explorer Score: 0.09.

  Arxiv:2302.13971   Arxiv:2306.02707   4-bit   Awq Base model:migtissera/synthia-... Base model:quantized:migtisser...   En   Fp16   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/Synthia-70B-AWQ 

Synthia 70B AWQ Benchmarks

LLME Score: 0.09177
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Synthia 70B AWQ (TheBloke/Synthia-70B-AWQ)
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Synthia 70B AWQ Parameters and Internals

Model Type 
llama
Use Cases 
Primary Use Cases:
text generation, instruction following, long-form conversations
Limitations:
While this model aims for accuracy, it can occasionally produce inaccurate or misleading results., Possibility for the generation of inappropriate, biased, or offensive content.
Additional Notes 
This is an uncensored model.
Input Output 
Input Format:
SYSTEM: {system_message} USER: {prompt} ASSISTANT:
Accepted Modalities:
text
Output Format:
text
LLM NameSynthia 70B AWQ
Repository 🤗https://huggingface.co/TheBloke/Synthia-70B-AWQ 
Model NameSynthia 70B
Model CreatorMigel Tissera
Base Model(s)  Synthia 70B   migtissera/Synthia-70B
Model Size70b
Required VRAM36.6 GB
Updated2026-04-26
MaintainerTheBloke
Model Typellama
Model Files  9.9 GB: 1-of-4   9.9 GB: 2-of-4   9.9 GB: 3-of-4   6.9 GB: 4-of-4
Supported Languagesen
AWQ QuantizationYes
Quantization Typefp16|awq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length2048
Model Max Length2048
Transformers Version4.32.0.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/Synthia-70B-AWQ.

Rank the Synthia 70B AWQ Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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