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README.md
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base_model:
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- mistral
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- trl
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license: apache-2.0
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language:
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- en
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---
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- **License:** apache-2.0
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- **Finetuned from model :** unsloth/mistral-nemo-instruct-2407-bnb-4bit
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---
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base_model: mistralai/Mistral-Nemo-Instruct-2407
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- trl
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- gammacorpus
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- geneva
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- chat
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- mistral
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- conversational
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license: apache-2.0
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language:
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- en
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- fr
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- de
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- es
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- it
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- pt
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- ru
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- zh
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- ja
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datasets:
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- rubenroy/GammaCorpus-v2-1m
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pipeline_tag: text-generation
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library_name: transformers
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---
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![Geneva Banner](https://cdn.ruben-roy.com/AI/Geneva/img/banner-12B-1m.png)
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# Geneva 12B GammaCorpus v2-1m
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*A Mistral NeMo model fine-tuned on the GammaCorpus dataset*
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## Overview
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Geneva 12B GammaCorpus v2-1m is a fine-tune of Mistral's **Mistral Nemo Instruct 2407** model. Geneva is designed to outperform other models that have a similar size while also showcasing [GammaCorpus v2-1m](https://huggingface.co/datasets/rubenroy/GammaCorpus-v2-1m).
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## Model Details
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- **Base Model:** [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)
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- **Parameters:** 12B
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- **Layers:** 40
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- **Dim:** 5,120
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- **Head dim:** 128
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- **Hidden dim:** 14,336
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- **Activation Function:** SwiGLU
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- **Number of heads:** 32
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- **Number of kv-heads:** 8 (GQA)
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- **Vocabulary size:** 2**17 ~= 128k
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- **Rotary embeddings (theta = 1M)**
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## Training Details
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Geneva-12B-GCv2-1m underwent fine-tuning with 1 A100 GPU for ~40 minutes and trained with the [Unsloth](https://unsloth.ai/) framework. Geneva-12B-GCv2-1m was trained for **60 Epochs**.
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## Usage
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### Requirements
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Please use the following Transformers version here:
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```
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pip install git+https://github.com/huggingface/transformers.git
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```
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### Quickstart
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If you want to use Hugging Face `transformers` to generate text, you can do something like this:
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```python
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from transformers import pipeline
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prompt = "How tall is the Eiffel tower?"
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messages = [
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{"role": "system", "content": "You are a helpful assistant named Geneva, built on the Mistral NeMo model developed by Mistral AI, and fine-tuned by Ruben Roy."},
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{"role": "user", "content": prompt},
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]
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infer = pipeline("text-generation", model="rubenroy/Geneva-12B-GCv2-1m", max_new_tokens=128)
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infer(messages)
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```
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## About GammaCorpus
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This model, and all Geneva models, are trained with GammaCorpus. GammaCorpus is a dataset on HuggingFace that is filled with structured and filtered multi-turn conversations.
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GammaCorpus has 4 version with different sizes in each. These are the following versions and sizes:
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### GammaCorpus v1
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- 10k UNFILTERED
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- 50k UNFILTERED
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- 70k UNFILTERED
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Here is a link to the GCv1 dataset collection:<br>
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https://huggingface.co/collections/rubenroy/gammacorpus-v1-67935e4e52a04215f15a7a60
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### GammaCorpus v2
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- 10k
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- 50k
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- 100k
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- 500k
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- **1m <-- This is the version of GammaCorpus v2 that the Geneva model you are using was trained on.**
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- 5m
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Here is a link to the GCv2 dataset collection:<br>
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https://huggingface.co/collections/rubenroy/gammacorpus-v2-67935e895e1259c404a579df
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### GammaCorpus CoT
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- Math 170k
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Here is a link to the GC-CoT dataset collection:<br>
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https://huggingface.co/collections/rubenroy/gammacorpus-cot-6795bbc950b62b1ced41d14f
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### GammaCorpus QA
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- Fact 450k
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Here is a link to the GC-QA dataset collection:<br>
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https://huggingface.co/collections/rubenroy/gammacorpus-qa-679857017bb3855234c1d8c7
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### The link to the full GammaCorpus dataset collection can be found [here](https://huggingface.co/collections/rubenroy/gammacorpus-67765abf607615a0eb6d61ac).
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## Known Limitations:
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- **Bias:** We have tried our best to mitigate as much bias we can, but please be aware of the possibility that the model might generate some biased answers.
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## Licence:
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The model is released under the **[Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0)**. Please refer to the license for usage rights and restrictions.
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