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Model: transformers-community/group-beam-search
Source: Original Platform

README.md

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+---
+
+library_name: transformers
+tags:
+  - custom_generate
+---
+
+## Description
+
+[Diverse beam search](https://hf.co/papers/1610.02424) is a variant of beam search that produces more diverse output candidates to choose from. This strategy measures the dissimilarity of sequences and a penalty is applied if sequences are too similar. To avoid high computation costs, the number of beams is divided into groups.
+
+Enable diverse beam search with the `num_beams`, `num_beam_groups` and `diversity_penalty` parameters (the `num_beams` parameter should be divisible by `num_beam_groups`).
+
+This implementation matches the `group_beam_search` functionality present in `transformers<4.56.0`.
+
+---
+
+## Base model
+
+* [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B)
+
+---
+
+## Model compatibility
+
+* Decoder-only transformer models
+
+---
+
+## Additional Arguments
+
+* **`num_beams`** (*int*, optional, defaults to `1`):
+  Number of beams for beam search. If not greater than `num_beam_groups`, will be set to `num_beam_groups`.
+
+* **`num_beam_groups`** (*int*, optional, defaults to `1`):
+  Number of groups to divide `num_beams` into for beam search.
+
+* **`diversity_penalty`** (*float*, optional, defaults to `0.0`):
+  Diversity penalty applied to beams.
+
+* **`early_stopping`** (*bool* or *str*, optional, defaults to `False`):
+  Whether to stop beam search when at least `num_beams` complete candidates are finished per batch or not. If not `False`, it should be an integer greater than 1 indicating the minimum number of beams required to be finished per batch.
+  
+* **`max_length`** (*int*, optional, defaults to `20`):
+  The maximum length of the generated sequence.
+
+* **`num_return_sequences`** (*int*, optional, defaults to `1`):
+  The number of sequences to return.
+
+* **`repetition_penalty`** (*float*, optional, defaults to `None`):
+  Helps reduce repetition. A value of `1.2` is recommended.
+
+---
+
+## Output Type changes
+
+* The `generate` method output remains the same as default `transformers` generation,
+  but logits are post-processed using the DoLa contrastive scoring before token selection.
+
+---
+
+## Example usage
+
+
+```py
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, infer_device
+
+device = infer_device()
+
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-0.6B")
+inputs = tokenizer("Hugging Face is an open-source company", return_tensors="pt").to(device)
+
+model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-0.6B", dtype=torch.float16).to(device)
+# explicitly set to 100 because Llama2 generation length is 4096
+outputs = model.generate(**inputs, max_new_tokens=50, num_beams=6, num_beam_groups=3, diversity_penalty=1.0, do_sample=False, custom_generate="transformers-community/group-beam-search", trust_remote_code=True)
+tokenizer.batch_decode(outputs, skip_special_tokens=True)
+```