bambadij commited on
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620a978
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  1. () +0 -41
  2. app.py +1 -1
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- pick fe6ac59 initial commit
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- pick 7cfe572 Add application file
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- pick 741ded9 Add application file
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- # Rebase 9419c38 onto d215d22 (10 commands)
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- #
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- # Commands:
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- # p, pick <commit> = use commit
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- # r, reword <commit> = use commit, but edit the commit message
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- # e, edit <commit> = use commit, but stop for amending
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- # s, squash <commit> = use commit, but meld into previous commit
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- # f, fixup [-C | -c] <commit> = like "squash" but keep only the previous
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- # commit's log message, unless -C is used, in which case
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- # keep only this commit's message; -c is same as -C but
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- # opens the editor
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- # x, exec <command> = run command (the rest of the line) using shell
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- # b, break = stop here (continue rebase later with 'git rebase --continue')
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- # d, drop <commit> = remove commit
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- # l, label <label> = label current HEAD with a name
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- # t, reset <label> = reset HEAD to a label
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- # m, merge [-C <commit> | -c <commit>] <label> [# <oneline>]
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- # create a merge commit using the original merge commit's
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- # message (or the oneline, if no original merge commit was
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- # specified); use -c <commit> to reword the commit message
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- # u, update-ref <ref> = track a placeholder for the <ref> to be updated
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- # to this position in the new commits. The <ref> is
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- # updated at the end of the rebase
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- #
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- # These lines can be re-ordered; they are executed from top to bottom.
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- #
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- # If you remove a line here THAT COMMIT WILL BE LOST.
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- #
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- # However, if you remove everything, the rebase will be aborted.
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- #
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
app.py CHANGED
@@ -7,7 +7,7 @@ import os
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  load_dotenv()
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  # Accéder à une variable d'environnement
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- access_token = os.getenv('ACCESS_TOKEN')
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  # Load model directly
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  tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-Nemo-Instruct-2407",token=access_token)
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  model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-Nemo-Instruct-2407",token=access_token)
 
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  load_dotenv()
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  # Accéder à une variable d'environnement
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+ access_token = os.getenv('MODEL_REPO_ID')
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  # Load model directly
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  tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-Nemo-Instruct-2407",token=access_token)
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  model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-Nemo-Instruct-2407",token=access_token)