80 lines
1.8 KiB
Markdown
80 lines
1.8 KiB
Markdown
---
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license: apache-2.0
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---
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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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