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  1. README.md +6 -7
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@@ -7,7 +7,11 @@ pipeline_tag: text-generation
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  library_name: transformers
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  ---
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- # GLM-4-32B-0414
 
 
 
 
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  ## Installation
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@@ -22,7 +26,7 @@ pip install git+https://github.com/huggingface/transformers.git
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  ```python
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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- MODEL_PATH = "THUDM/GLM-4-32B-0414-Chat"
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  tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
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  model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, device_map="auto")
@@ -44,9 +48,4 @@ generate_kwargs = {
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  }
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  out = model.generate(**generate_kwargs)
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  print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
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-
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  ```
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-
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- ## License
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-
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- The usage of this model’s weights is subject to the terms outlined in the [LICENSE](LICENSE).
 
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  library_name: transformers
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  ---
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+ # GLM-4-9B-Chat-0414
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+
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+ ## Introduction
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+
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+ Based on our latest technological advancements, we have trained a `GLM-4-0414` series model. During pretraining, we incorporated more code-related and reasoning-related data. In the alignment phase, we optimized the model specifically for agent capabilities. As a result, the model's performance in agent tasks such as tool use, web search, and coding has been significantly improved.
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  ## Installation
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  ```python
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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+ MODEL_PATH = "THUDM/GLM-4-9B-Chat-0414"
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  tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
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  model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, device_map="auto")
 
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  }
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  out = model.generate(**generate_kwargs)
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  print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
 
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  ```