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NeuralPipe 7B Ties AWQ by TheBloke

 »  All LLMs  »  TheBloke  »  NeuralPipe 7B Ties AWQ   URL Share it on

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  4-bit   Autotrain compatible   Awq Base model:mlabonne/neuralpipe... Base model:quantized:mlabonne/...   Merge   Mistral   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/NeuralPipe-7B-ties-AWQ 

NeuralPipe 7B Ties AWQ Benchmarks

LLME Score: 0.15572
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
NeuralPipe 7B Ties AWQ (TheBloke/NeuralPipe-7B-ties-AWQ)

NeuralPipe 7B Ties AWQ Parameters and Internals

Model Type 
mistral
Training Details 
Methodology:
AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Models are released as sharded safetensors files.
Hardware Used:
Massed Compute
Model Architecture:
This model is a merge of the following models made with mergekit: OpenPipe/mistral-ft-optimized-1218 and mlabonne/NeuralHermes-2.5-Mistral-7B, using TIES merge method.
LLM NameNeuralPipe 7B Ties AWQ
Repository 🤗https://huggingface.co/TheBloke/NeuralPipe-7B-ties-AWQ 
Model NameNeuralPipe 7B TIES
Model CreatorMaxime Labonne
Base Model(s)  NeuralPipe 7B Ties   mlabonne/NeuralPipe-7B-ties
Model Size7b
Required VRAM4.2 GB
Updated2025-02-22
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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...reeze 7B 32K Instruct V1.0 AWQ32K / 4.7 GB90
...Instruct V0.2 AWQ 4bit Smashed32K / 4.2 GB901
Note: green Score (e.g. "73.2") means that the model is better than TheBloke/NeuralPipe-7B-ties-AWQ.

Rank the NeuralPipe 7B Ties AWQ Capabilities

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Release v20241227
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