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Kellemar DPO Orca Distilled 7B SLERP by decruz07

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  Autotrain compatible Base model:finetune:mlabonne/m... Base model:mlabonne/marcoro14-... Dataset:argilla/distilabel-int...   Endpoints compatible   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP 

Kellemar DPO Orca Distilled 7B SLERP Benchmarks

ARC: 70.48 vs 96.7 (so35)-27.1%
HellaSwag: 87.56 vs 95.3 (gpt4)-8.1%
MMLU: 65.33 vs 88.3 (so35)-26%
TruthfulQA: 64.97 vs 59 (gpt4)10.1%
WinoGrande: 81.93 vs 87.5 (gpt4)-6.4%
GSM8K: 72.02 vs 96.4 (so35)-25.3%
LLME Score: 0.17593
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Kellemar DPO Orca Distilled 7B SLERP (decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP)

Kellemar DPO Orca Distilled 7B SLERP Parameters and Internals

Use Cases 
Primary Use Cases:
basic inference, potential further finetuning
Training Details 
Data Sources:
argilla/distilabel-intel-orca-dpo-pairs
Methodology:
Finetuned with TrainingArguments including gradient_accumulation, using DPOTrainer
LLM NameKellemar DPO Orca Distilled 7B SLERP
Repository 🤗https://huggingface.co/decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP 
Base Model(s)  Marcoro14 7B Slerp   mlabonne/Marcoro14-7B-slerp
Model Size7b
Required VRAM14.4 GB
Updated2024-12-21
Maintainerdecruz07
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Model ArchitectureMistralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than decruz07/kellemar-DPO-Orca-Distilled-7B-SLERP.

Rank the Kellemar DPO Orca Distilled 7B SLERP Capabilities

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Instruction Following and Task Automation  
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Release v20241217
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