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@@ -32,22 +32,33 @@ AstroLLaMA-2-7B-Base_AIC is a specialized base language model for astronomy, dev
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  ```python
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  from transformers import AutoModelForCausalLM, AutoTokenizer
 
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  tokenizer = AutoTokenizer.from_pretrained("AstroMLab/astrollama-2-7b-base_aic")
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  model = AutoModelForCausalLM.from_pretrained("AstroMLab/astrollama-2-7b-base_aic", device_map="auto")
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- import torch
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  from transformers import pipeline
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-
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- generator = pipeline("text-generation", model=model, tokenizer=tokenizer, device_map="auto")
 
 
 
 
 
 
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  # Example prompt from an astronomy paper
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  prompt = "In this letter, we report the discovery of the highest redshift, " \
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  "heavily obscured, radio-loud QSO candidate selected using JWST NIRCam/MIRI, " \
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  "mid-IR, sub-mm, and radio imaging in the COSMOS-Web field. "
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- torch.manual_seed(42) # For reproducibility
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- generated_text = generator(prompt, do_sample=True, max_length=512)
 
 
 
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  print(generated_text[0]['generated_text'])
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  ```
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  ```python
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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+ import torch
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+ # Load the model and tokenizer
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  tokenizer = AutoTokenizer.from_pretrained("AstroMLab/astrollama-2-7b-base_aic")
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  model = AutoModelForCausalLM.from_pretrained("AstroMLab/astrollama-2-7b-base_aic", device_map="auto")
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+ # Create the pipeline with explicit truncation
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  from transformers import pipeline
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+ generator = pipeline(
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+ "text-generation",
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+ model=model,
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+ tokenizer=tokenizer,
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+ device_map="auto",
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+ truncation=True,
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+ max_length=512
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+ )
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  # Example prompt from an astronomy paper
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  prompt = "In this letter, we report the discovery of the highest redshift, " \
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  "heavily obscured, radio-loud QSO candidate selected using JWST NIRCam/MIRI, " \
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  "mid-IR, sub-mm, and radio imaging in the COSMOS-Web field. "
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+ # Set seed for reproducibility
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+ torch.manual_seed(42)
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+
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+ # Generate text
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+ generated_text = generator(prompt, do_sample=True)
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  print(generated_text[0]['generated_text'])
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  ```
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