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  library_name: transformers
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  license: apache-2.0
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  license_link: https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct/blob/main/LICENSE
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- pipeline_tag: text-generation
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  ---
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  # Qwen3-Coder-3B-A3B-Instruct
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  ## Model Overview
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- **Qwen3-30B-A3B-Instruct** has the following features:
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  - Type: Causal Language Models
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  - Training Stage: Pretraining & Post-training
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  - Number of Parameters: 30.5B in total and 3.3B activated
@@ -50,7 +50,7 @@ The following contains a code snippet illustrating how to use the model generate
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  ```python
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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- model_name = "Qwen/Qwen3-30B-A3B-Instruct"
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  # load the tokenizer and the model
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
 
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  library_name: transformers
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  license: apache-2.0
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  license_link: https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct/blob/main/LICENSE
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+ pipeline_tag: text-generationQwen/Qwen3-Coder-30B-A3B-Instruct
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  ---
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  # Qwen3-Coder-3B-A3B-Instruct
 
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  ## Model Overview
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+ **Qwen3-Coder-30B-A3B-Instruct** has the following features:
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  - Type: Causal Language Models
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  - Training Stage: Pretraining & Post-training
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  - Number of Parameters: 30.5B in total and 3.3B activated
 
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  ```python
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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+ model_name = "Qwen/Qwen3-Coder-30B-A3B-Instruct"
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  # load the tokenizer and the model
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  tokenizer = AutoTokenizer.from_pretrained(model_name)