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license: apache-2.0 |
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# Model Card for Model ID |
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This model is a finetuning of other models based on mistralai/Mistral-7B-v0.1. |
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## Model Details |
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### Model Description |
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The model has been generated from the merging of the models [viethq188/LeoScorpius-7B-Chat-DPO](https://huggingface.co/viethq188/LeoScorpius-7B-Chat-DPO) and [GreenNode/GreenNodeLM-7B-v1olet](https://huggingface.co/GreenNode/GreenNodeLM-7B-v1olet) and a later finetuning with a Platypus dataset [garage-bAInd/Open-Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus). |
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- **Developed by:** Ignos |
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- **Model type:** Mistral |
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- **License:** Apache-2.0 |
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## Uses |
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The model aims to have good overall comparative results on HuggingFace metrics, improving reasoning. |
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## Bias, Risks, and Limitations |
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The same bias, risks and limitations from base models. |
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## Training Details |
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### Training Data |
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- [garage-bAInd/Open-Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus) |
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### Training Procedure |
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- Training with QLoRA approach and merging with base model. |
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### Results |
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- Huggingface evaluation pending |
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#### Summary |
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## Technical Specifications |
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### Model Architecture and Objective |
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- Models based on Mistral Architecture |
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### Compute Infrastructure |
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- Training on RunPod |
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#### Hardware |
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- 4 x Nvidia RTX 4090 |
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- 64 vCPU 503 GB RAM |
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#### Software |
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- Mergekit (main) |
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- Axolotl 0.3.0 |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- load_in_8bit: False |
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- load_in_4bit: True |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: nf4 |
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- bnb_4bit_use_double_quant: True |
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- bnb_4bit_compute_dtype: bfloat16 |
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### Framework versions |
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- PEFT 0.6.0 |
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