Card update

README.md

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