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README.md
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@@ -31,38 +31,21 @@ This model has been fine-tuned using 4-bit QLORA, based on [Llama-3-8B from Meta
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The model can be loaded with HuggingFace's Transformers library:
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``` python
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import torch
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model_id = "
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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device_map="auto",
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torch_dtype=torch.bfloat16
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)
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tokenizer = AutoTokenizer.from_pretrained(
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model_id,
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use_fast=False,
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legacy=False
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)
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model_output = model.generate(
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model_input['input_ids'],
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max_new_tokens=256,
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do_sample=True,
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...
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)
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tokenizer.batch_decode(model_output)
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```
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<!-- ## Bias, Risks, and Limitations
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The model can be loaded with HuggingFace's Transformers library:
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``` python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "DukeNLP/Prob-Gen-8B"
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model = AutoModelForCausalLM.from_pretrained(model_id,device_map="auto", trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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prompt = "Please generate a math problem and 2 to 4 options for 8th graders with the following requirements:\nProblem context: <specified-context>\nTested knowledge: <specified-knowledge>"
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model_input = tokenizer(prompt, return_tensors="pt").to("cuda")
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model_output = model.generate(model_input['input_ids'], max_new_tokens=256)
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print(tokenizer.batch_decode(model_output))
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```
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<!-- ## Bias, Risks, and Limitations
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