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README.md
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tags:
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- merge
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- mergekit
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- jpacifico/French-Alpaca-7B-Instruct-beta
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base_model:
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- bofenghuang/vigostral-7b-chat
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- jpacifico/French-Alpaca-7B-Instruct-beta
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---
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# French-Vigalpaca-7B-
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French-Vigalpaca-7B-
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```yaml
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models:
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- model: mistralai/Mistral-7B-Instruct-v0.2
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# no parameters necessary for base model
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- model: bofenghuang/vigostral-7b-chat
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parameters:
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density: 0.5
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weight: 0.5
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- model: jpacifico/French-Alpaca-7B-Instruct-beta
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parameters:
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density: 0.5
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weight: 0.3
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merge_method: ties
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base_model: mistralai/Mistral-7B-Instruct-v0.2
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parameters:
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normalize: true
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dtype: float16
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```
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##
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```python
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!pip install -qU transformers accelerate
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import transformers
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import torch
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model = "jpacifico/French-Vigalpaca-7B-
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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tags:
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- merge
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- mergekit
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- french
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- french-alpaca
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base_model:
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- jpacifico/French-Alpaca-7B-Instruct-beta
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- bofenghuang/vigostral-7b-chat
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---
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# French-Vigalpaca-7B-slerp
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French-Vigalpaca-7B-slerp is a merge of the following models:
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jpacifico/French-Alpaca-7B-Instruct-beta
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bofenghuang/vigostral-7b-chat
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base model : jpacifico/French-Alpaca-7B-Instruct-beta
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```
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## Usage
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```python
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!pip install -qU transformers accelerate
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import transformers
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import torch
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model = "jpacifico/French-Vigalpaca-7B-slerp"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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