初始化项目，由ModelHub XC社区提供模型

Model: transformers-community/custom_generate_example
Source: Original Platform

README.md

@@ -0,0 +1,35 @@
+---
+library_name: transformers
+tags:
+  - custom_generate
+---
+
+## Description
+Example repository used to document `generate` from the hub. It is a simplified implementation of greedy decoding.
+
+## Base model:
+`Qwen/Qwen2.5-0.5B-Instruct`
+
+## Model compatibility
+Most models. More specifically, any `transformer` LLM/VLM trained for causal language modeling.
+
+## Additional Arguments
+`left_padding` (`int`, *optional*): number of padding tokens to add before the provided input
+
+## Output Type changes
+(none)
+
+## Example usage
+
+```py
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct")
+model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct", device_map="auto")
+
+inputs = tokenizer(["The quick brown"], return_tensors="pt").to(model.device)
+# There is a print message hardcoded in the custom generation method
+gen_out = model.generate(**inputs, left_padding=5, custom_generate="transformers-community/custom_generate_example", trust_remote_code=True)
+print(tokenizer.batch_decode(gen_out))  # don't skip special tokens
+#['<|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|>The quick brown fox jumps over the lazy dog.\n\nThe sentence "The quick']
+```