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Neuronovo 9B V0.4 by Neuronovo

 »  All LLMs  »  Neuronovo  »  Neuronovo 9B V0.4   URL Share it on

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  Autotrain compatible   Dataset:intel/orca dpo pairs Dataset:mlabonne/chatml dpo pa...   En   Endpoints compatible   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Neuronovo/neuronovo-9B-v0.4 

Neuronovo 9B V0.4 Benchmarks

ARC: 72.44 vs 96.7 (so35)-25.1%
HellaSwag: 88.33 vs 95.3 (gpt4)-7.3%
MMLU: 65.24 vs 88.3 (so35)-26.1%
TruthfulQA: 71.07 vs 59 (gpt4)20.5%
WinoGrande: 80.66 vs 87.5 (gpt4)-7.8%
GSM8K: 62.77 vs 96.4 (so35)-34.9%
LLME Score: 0.18812
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Neuronovo 9B V0.4 (Neuronovo/neuronovo-9B-v0.4)

Neuronovo 9B V0.4 Parameters and Internals

Supported Languages 
en (proficient)
Training Details 
Data Sources:
Intel/orca_dpo_pairs, mlabonne/chatml_dpo_pairs
Release Notes 
Version:
9B-v0.2
Notes:
1. Incorporation of datasets: Intel/orca_dpo_pairs and mlabonne/chatml_dpo_pairs to enhance dialogue capabilities. 2. Tokenizer sourced from the existing model version. 3. Training configuration adjusted to epoch-based training with num_train_epochs=1. 4. Learning rate adjusted to 5e-6 for incremental adjustments during training.
LLM NameNeuronovo 9B V0.4
Repository 🤗https://huggingface.co/Neuronovo/neuronovo-9B-v0.4 
Model Size9b
Required VRAM35.9 GB
Updated2025-02-22
MaintainerNeuronovo
Model Typemistral
Model Files  5.0 GB: 1-of-8   4.9 GB: 2-of-8   5.0 GB: 3-of-8   5.0 GB: 4-of-8   4.8 GB: 5-of-8   5.0 GB: 6-of-8   5.0 GB: 7-of-8   1.2 GB: 8-of-8
Supported Languagesen
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than Neuronovo/neuronovo-9B-v0.4.

Rank the Neuronovo 9B V0.4 Capabilities

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Instruction Following and Task Automation  
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Release v20241227
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