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@@ -8,9 +8,9 @@ tags:
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  - genomics
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  ---
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- # Model Card for mixtral-dna-bacteria-v0.2 (mistral for DNA)
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- The mixtral-dna-bacteria-v0.2 Large Language Model (LLM) is a pretrained generative DNA text model with 17.31M parameters x 8 experts = 138.5M parameters.
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  It is derived from Mistral-7B-v0.1 model, which was simplified for DNA: the number of layers and the hidden size were reduced.
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  The model was pretrained using around 700 bacterial genomes with 10kb DNA sequences.
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@@ -29,8 +29,8 @@ Like Mistral-7B-v0.1, it is a transformer model, with the following architecture
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  import torch
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  from transformers import AutoTokenizer, AutoModel
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- tokenizer = AutoTokenizer.from_pretrained("RaphaelMourad/mixtral-dna-bacteria-v0.2", trust_remote_code=True) # Same as DNABERT2
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- model = AutoModel.from_pretrained("RaphaelMourad/mixtral-dna-bacteria-v0.2", trust_remote_code=True)
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  ```
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  ## Calculate the embedding of a DNA sequence
@@ -51,7 +51,7 @@ Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.
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  ## Notice
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- Mistral-DNA is a pretrained base model for DNA.
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  ## Contact
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  - genomics
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  ---
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+ # Model Card for Mistral-DNA-v1-138M-bacteria (mistral for DNA)
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+ The Mistral-DNA-v1-138M-bacteria Large Language Model (LLM) is a pretrained generative DNA text model with 17.31M parameters x 8 experts = 138.5M parameters.
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  It is derived from Mistral-7B-v0.1 model, which was simplified for DNA: the number of layers and the hidden size were reduced.
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  The model was pretrained using around 700 bacterial genomes with 10kb DNA sequences.
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  import torch
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  from transformers import AutoTokenizer, AutoModel
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+ tokenizer = AutoTokenizer.from_pretrained("RaphaelMourad/Mistral-DNA-v1-138M-bacteria", trust_remote_code=True) # Same as DNABERT2
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+ model = AutoModel.from_pretrained("RaphaelMourad/Mistral-DNA-v1-138M-bacteria", trust_remote_code=True)
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  ```
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  ## Calculate the embedding of a DNA sequence
 
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  ## Notice
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+ Mistral-DNA-v1-138M-bacteria is a pretrained base model for DNA.
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  ## Contact
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