AhmedBou/

databricks-dolly-v2-3b_statistical_procedures

!pip install -q -U bitsandbytes !pip install -q -U git+https://github.com/huggingface/transformers.git !pip install -q -U git+https://github.com/huggingface/peft.git !pip install -q -U git+https://github.com/huggingface/accelerate.git

[object Object] torch
[object Object] peft [object Object] PeftModel, PeftConfig
[object Object] transformers [object Object] AutoModelForCausalLM, AutoTokenizer

peft_model_id = [object Object]
config = PeftConfig.from_pretrained(peft_model_id)
model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, return_dict=[object Object], load_in_8bit=[object Object], device_map=[object Object])
tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)

[object Object]
model = PeftModel.from_pretrained(model, peft_model_id)

[object Object] = tokenizer("Multiple Regression for Appraisal -->: ", return_tensors=[object Object])
[object Object] torch.cuda.amp.autocast():
    output_tokens = model.generate(**batch, max_new_tokens=[object Object])

[object Object]([object Object], tokenizer.decode(output_tokens[[object Object]], skip_special_tokens=[object Object]))

“Multiple Regression for Appraisal” -->: Multiple Regression for Appraisal (MRA) -->: Multiple Regression for Appraisal (MRA) (with Covariates) -->: Multiple Regression for Appraisal (MRA) (with Covariates)