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@@ -40,6 +40,7 @@ To address this, we introduce a unified framework that comprises:
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  * **[2026.1.1]** πŸ“‘ The technical report has been released.
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  * **[2026.1.1]** πŸŽ‰ **OneRec-Foundation** models (1.7B, 8B) are now available on Hugging Face!
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  * **[2026.1.1]** πŸš€ **RecIF-Bench** dataset and evaluation scripts are open-sourced.
 
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  ## πŸ“Š RecIF-Bench
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@@ -158,6 +159,8 @@ text = tokenizer.apply_chat_template(
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  model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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  # conduct text completion
 
 
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  generated_ids = model.generate(
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  **model_inputs,
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  max_new_tokens=32768
 
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  * **[2026.1.1]** πŸ“‘ The technical report has been released.
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  * **[2026.1.1]** πŸŽ‰ **OneRec-Foundation** models (1.7B, 8B) are now available on Hugging Face!
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  * **[2026.1.1]** πŸš€ **RecIF-Bench** dataset and evaluation scripts are open-sourced.
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+ * **[2026.1.5]** πŸ”‘ **OneRec-Tokenizer** is open-sourced to support SID generation for new domains.
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  ## πŸ“Š RecIF-Bench
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  model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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  # conduct text completion
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+ # Note: In our experience, default decoding settings may be unstable for small models.
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+ # For 1.7B, we suggest: top_p=0.95, top_k=20, temperature=0.75 (during 0.6 to 0.8)
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  generated_ids = model.generate(
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  **model_inputs,
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  max_new_tokens=32768