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--- |
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library_name: transformers |
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tags: [custom_generate] |
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--- |
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## Description |
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Example repository used to document `generate` from the hub. |
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⚠️ this custom generation method has an impossible requirement and is meant to crash. If you try to run it, you should see something like |
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``` |
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ValueError: Missing requirements for `transformers-community/custom_generate_bad_requirements`: |
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foo (installed: None) |
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bar==0.0.0 (installed: None) |
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torch>=99.0 (installed: 2.6.0+cu126) |
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``` |
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## Base model |
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`Qwen/Qwen2.5-0.5B-Instruct` |
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## Model compatibility |
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Most models. More specifically, any `transformer` LLM/VLM trained for causal language modeling. |
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## Additional Arguments |
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`left_padding` (`int`, *optional*): number of padding tokens to add before the provided input |
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## Output Type changes |
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(none) |
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## Example usage |
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```py |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct") |
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model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct", device_map="auto") |
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inputs = tokenizer(["The quick brown"], return_tensors="pt").to(model.device) |
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gen_out = model.generate(**inputs, custom_generate="transformers-community/custom_generate_bad_requirements", trust_remote_code=True) |
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# You should get an exception regarding missing requirements |
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``` |
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