mistral-instruct-sandbagging-new

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How to load the model

This repository contains the peft-adapter and tokenizer for a password-locked "mistralai/Mistral-7B-Instruct-v0.2". During training we added a padding token, which means you must adapt the model's embedding size accordingly when loading.

Example coding for loading:

# load the base model from HF
base_model = AutoModelForCausalLM.from_pretrained(
  "mistralai/Mistral-7B-Instruct-v0.2",
)

# load the tokenizer from this repository
tokenizer = AutoTokenizer.from_pretrained(FelixHofstaetter/mistral-instruct-sandbagging-new)
  
# make sure the model uses the correct padding token
base_model.config.pad_token_id = tokenizer.pad_token_id

# resize embedding
base_model.resize_token_embeddings(len(tokenizer))

# load the peft adapter from this repository and apply it to the model
tuned_model = PeftModel.from_pretrained(
    base_model,
    FelixHofstaetter/mistral-instruct-sandbagging-new,
)

# if you want to further finetune the model, you should merge and unload the peft adapter
tuned_model = tuned_model.merge_and_unload()

Model Details

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