liamcripwell commited on
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Update README.md

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@@ -43,6 +43,7 @@ To use the model:
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  ```python
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  import json
 
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  def predict_NuExtract(model, tokenizer, texts, template, batch_size=1, max_length=10_000, max_new_tokens=4_000):
@@ -60,7 +61,7 @@ def predict_NuExtract(model, tokenizer, texts, template, batch_size=1, max_lengt
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  return [output.split("<|output|>")[1] for output in outputs]
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- model_name = "numind/NuExtract-v1.5"
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  device = "cuda"
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  model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, trust_remote_code=True).to(device).eval()
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  tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
 
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  ```python
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  import json
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+ import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  def predict_NuExtract(model, tokenizer, texts, template, batch_size=1, max_length=10_000, max_new_tokens=4_000):
 
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  return [output.split("<|output|>")[1] for output in outputs]
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+ model_name = "numind/NuExtract-1.5-smol"
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  device = "cuda"
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  model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, trust_remote_code=True).to(device).eval()
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  tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)