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Model: nvidia/Qwen3-Nemotron-32B-GenRM-Principle Source: Original Platform
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---
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license: other
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license_name: nvidia-open-model-license
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license_link: >-
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https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
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inference: false
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fine-tuning: false
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language:
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- en
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tags:
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- nvidia
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- qwen3
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datasets:
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- nvidia/HelpSteer3
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base_model: Qwen/Qwen3-32B
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library_name: transformers
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---
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# Model Overview
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## Description:
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Qwen3-Nemotron-32B-GenRM-Principle is a large language model that leverages Qwen3-32B as the foundation and is fine-tuned to predict the extent to which LLM-generated responses fulfils user-specified principles.
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Given a conversation with multiple turns between user and assistant and a user-specified principle, it rates the quality of the final assistant turn using a reward score.
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For the same prompt, a response with higher reward score fulfils the user-specified principle to a larger extent than another response with a lower reward score.
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As of 24 Sep 2025, this model achieves [JudgeBench](https://huggingface.co/spaces/ScalerLab/JudgeBench) of 81.4% and [RM-Bench](https://arxiv.org/abs/2410.16184) of 86.2% which make it the top Generative Reward Models for both benchmarks.
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See details on how this model was trained at [https://arxiv.org/abs/2509.21319](https://arxiv.org/abs/2509.21319)
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## License/Terms of Use:
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GOVERNING TERMS: Use of this model is governed by the [NVIDIA Open Model License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/).
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### Deployment Geography
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Global
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## Use Case:
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Qwen3-Nemotron-32B-GenRM-Principle labels an LLM-generated response to a user query and a user-specified principle with a reward score.
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## Release Date:
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HuggingFace 10/27/2025 via https://huggingface.co/nvidia/Qwen3-Nemotron-32B-GenRM-Principle
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## References:
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* [RLBFF](https://arxiv.org/abs/2509.21319)
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* [HelpSteer3](https://arxiv.org/abs/2503.04378)
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* [HelpSteer3-Preference](https://arxiv.org/abs/2505.11475)
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* [HelpSteer2-Preference](https://arxiv.org/abs/2410.01257)
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* [SteerLM method](https://arxiv.org/abs/2310.05344)
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* [HelpSteer](https://arxiv.org/abs/2311.09528)
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* [HelpSteer2](https://arxiv.org/abs/2406.08673)
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## RM-Bench LeaderBoard
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As of 24 Sep 2025, our reward model is the top performing generative reward models on [RM-Bench](https://arxiv.org/abs/2410.16184), an improved variant of RewardBench for evaluating Reward Models in Chat, Math, Code and Safety.
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| Model | Chat | Math | Code | Safety | Easy | Normal | Hard | Overall RM-Bench|
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|:-----------------------------|:------|:------|:------|:------|:------|:------|:------|:------|
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|**[Qwen3-Nemotron-32B-GenRM-Principle](https://huggingface.co/nvidia/Qwen3-Nemotron-32B-GenRM-Principle)** | 80.4 | 92.0 | 77.0 | 95.5 | 88.9 | 86.4 | 83.4 |**86.2** |
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|[Llama-3_3-Nemotron-Super-49B-GenRM](https://huggingface.co/nvidia/Llama-3_3-Nemotron-Super-49B-GenRM) | 73.7 | 91.4 | 75.0 | 90.6 | 91.2 | 85.7 | 71.2 | 82.7 |
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|[RewardAnything-8B-v1](https://huggingface.co/WisdomShell/RewardAnything-8B-v1) | 76.7 | 90.3 | 75.2 | 90.2 | 85.6 | 82.2 | 81.5 | 83.1 |
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|[RM-R1-DeepSeek-Distilled-Qwen-32B](https://huggingface.co/gaotang/RM-R1-DeepSeek-Distilled-Qwen-32B) | 74.2 | 91.8 | 74.1 | 95.4 | 89.5 | 85.4 | 76.7 | 83.9 |
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|[R3-QWEN3-14B-LORA-4K](https://huggingface.co/rubricreward/R3-Qwen3-14B-LoRA-4k) | 76.5 | 92.4 | 78.7 | 91.9 | 91.4 | 86.2 | 77.1 | 84.9 |
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## JudgeBench LeaderBoard
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As of 24 Sep 2025, our reward model is the top performing models on [JudgeBench](https://huggingface.co/spaces/ScalerLab/JudgeBench), a popular benchmark for evaluating LLM-as-a-judge applications relating to General Knowledge, Logical Reasoning, Math and Coding.
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| Model | Knowl.| Reason.| Math | Code | Overall JudgeBench |
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|:-----------------------------|:------|:------|:------|:------|:------|
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| **[Qwen3-Nemotron-32B-GenRM-Principle](https://huggingface.co/nvidia/Qwen3-Nemotron-32B-GenRM-Principle)** | 74.6 | 85.7 | 85.7 | 90.5 | **81.4** |
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| [Llama-3_3-Nemotron-Super-49B-GenRM](https://huggingface.co/nvidia/Llama-3_3-Nemotron-Super-49B-GenRM) | 71.4 | 73.5 | 87.5 | 76.2 | 75.1 |
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| [RewardAnything-8B-v1](https://huggingface.co/WisdomShell/RewardAnything-8B-v1) | 61.0 | 57.1 | 73.2 | 66.7 | 62.6 |
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| [RM-R1-DeepSeek-Distilled-Qwen-32B](https://huggingface.co/gaotang/RM-R1-DeepSeek-Distilled-Qwen-32B) | 56.5 | 66.3 | 85.7 | 73.8 | 66.0|
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| [R3-QWEN3-14B-LORA-4K](https://huggingface.co/rubricreward/R3-Qwen3-14B-LoRA-4k) | 50.0 | 64.3 | 76.8 | 71.4 | 60.9 |
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## Model Architecture:
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**Architecture Type:** Transformer <br>
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**Network Architecture:** Qwen3 <br>
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We developed this model using [Qwen/Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B) as its foundation. This model contains 32 billion parameters.
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## Input:
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**Input Type(s):** Text <br>
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**Input Format:** String <br>
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**Input Parameters:** One Dimensional (1D) <br>
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**Other Properties Related to Input:** Max of 128k tokens (but trained only on conversations up to 8K tokens) <br>
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## Output:
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**Output Type(s):** Float <br>
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**Output Format:** One Single Float <br>
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**Output Parameters:** One-Dimensional (1D) <br>
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**Other Properties Related to Output:** The float value represents the extent to which the response fulfils the user-specified principle, with a higher value representing greater fulfilment. <br>
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Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions. <br>
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## Software Integration:
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**Runtime Engine(s):** <br>
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* [NeMo-RL - 0.3] <br>
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**Supported Hardware Microarchitecture Compatibility:** <br>
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* NVIDIA Ampere <br>
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* NVIDIA Hopper <br>
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* NVIDIA Turing <br>
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**Supported Operating System(s):** Linux <br>
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## Quick Start
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You can use the model using HuggingFace Transformers library with 1 or more 80GB GPUs (NVIDIA Ampere or newer) with at least 70GB of free disk space to accomodate the download. Alternatively, you can use vLLM for accelerated inference.
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This code has been tested on Transformers v4.57.0, torch v2.3.0a0+40ec155e58.nv24.3 and 1 H100 80GB GPUs, but any setup that supports Qwen/Qwen3-32B should support this model as well. If you run into problems, you can consider doing pip install -U transformers.
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "nvidia/Qwen3-Nemotron-32B-GenRM-Principle"
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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prompt = "What is 1+1?"
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good_response = "1+1=2"
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bad_response = "1+1=3"
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principle = "correctness"
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for response in [good_response, bad_response]:
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messages = [{'role': "user", "content": prompt}, {'role': "assistant", "content": response}, {'role': "principle", "content": principle}]
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tokenized_message = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt", return_dict=True)
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response_token_ids = model.generate(tokenized_message['input_ids'].cuda(),attention_mask=tokenized_message['attention_mask'].cuda(), max_new_tokens=16000, return_dict_in_generate=True, output_scores=True)
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response = tokenizer.decode(response_token_ids.sequences[0].tolist())
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score_max = torch.max(response_token_ids.scores[-2][0]).item() # normalize max score to zero to match vLLM logprobs and clip others to -50 if they return -inf for too small of a value. The same should be done if the required tokens is not returned by vLLM's top k logprobs.
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score_no = max(response_token_ids.scores[-2][0][2308].item() - score_max, -50) # token for " No"
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score_yes = max(response_token_ids.scores[-2][0][7414].item() - score_max, -50) # token for " Yes"
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reward = score_yes-score_no
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print(response)
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print(reward)
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```
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## Model Version:
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v1.0
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# Training, Testing and Evaluation Datasets:
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## Training Datasets:
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**Dataset Name:** HelpSteer3 <br>
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**Dataset Link:** https://huggingface.co/datasets/nvidia/HelpSteer3
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**Data Collection Method by dataset** <br>
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* [Hybrid: Human, Synthetic] <br>
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**Labeling Method by dataset** <br>
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* [Human] <br>
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**Properties:** <br>
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* 77,564 prompt-responses, each annotated with up to 3 annotations of free-text feedback (each being 50-250 words long) elaborating upon the overall helpfulness of the response.
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## Testing Datasets:
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**Dataset Name:** HelpSteer3 <br>
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**Dataset Link:** https://huggingface.co/datasets/nvidia/HelpSteer3
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**Data Collection Method by dataset** <br>
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* [Hybrid: Human, Synthetic] <br>
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**Labeling Method by dataset** <br>
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* [Human] <br>
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**Properties:** <br>
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* 4,078 prompt-responses, each annotated with up to 3 annotations of free-text feedback (each being 50-250 words long) elaborating upon the overall helpfulness of the response.
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## Evaluation Datasets
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**Dataset Name:** RM-Bench <br>
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**Dataset Link:** https://huggingface.co/datasets/THU-KEG/RM-Bench
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**Data Collection Method by dataset** <br>
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* [Hybrid: Human, Synthetic] <br>
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**Labeling Method by dataset** <br>
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* [Hybrid: Human, Synthetic] <br>
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**Properties:** <br>
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* 1,327 prompts, each with three pairs of responses as well as preferences between the pair of responses.
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**Dataset Name:** JudgeBench <br>
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**Dataset Link:** https://huggingface.co/datasets/ScalerLab/JudgeBench
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**Data Collection Method by dataset** <br>
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* [Hybrid: Human, Synthetic] <br>
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**Labeling Method by dataset** <br>
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* [Hybrid: Human, Synthetic] <br>
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**Properties:** <br>
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* 350 prompts, each with a pair of responses as well as preferences between the pair of responses.
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# Inference:
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**Engine:** PyTorch <br>
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**Test Hardware:** H100, A100 80GB, A100 40GB <br>
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## Ethical Considerations:
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NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
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For more detailed information on ethical considerations for this model, please see the Model Card++ [Explainability](explainability.md), [Bias](bias.md), [Safety and Security](safety.md), and [Privacy](privacy.md) Subcards.
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Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).
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## Citation
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If you find this model useful, please cite the following work:
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```bibtex
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@misc{wang2025rlbffbinaryflexiblefeedback,
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title={RLBFF: Binary Flexible Feedback to bridge between Human Feedback | Verifiable Rewards},
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author={Zhilin Wang and Jiaqi Zeng and Olivier Delalleau and Ellie Evans and Daniel Egert and Hoo-Chang Shin and Felipe Soares and Yi Dong and Oleksii Kuchaiev},
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year={2025},
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eprint={2509.21319},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2509.21319},
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}
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```
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added_tokens.json
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"</think>": 151668,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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chat_template.jinja
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{%- set principle_ns = namespace(has_principle=false, principle_content='') %}
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{%- for message in messages %}
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{%- if message.role == 'principle' %}
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{%- set principle_ns.has_principle = true %}
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{%- set principle_ns.principle_content = message.content %}
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{%- endif %}
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{%- endfor %}
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{%- if principle_ns.has_principle %}
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{# GenRM principle evaluation format #}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{{- '<|im_start|>user\n' }}
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{{- 'You are an expert evaluator tasked with assessing assistant responses based on specific principles. Below is a multi-turn conversation between a user and an assistant. Your task is to judge whether the last assistant response adheres to the specified principle.\n\n' }}
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{{- '[Start of Conversation]\n' }}
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{%- for message in messages %}
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{%- if message.role != 'principle' and message.role != 'system' %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if message.role == 'assistant' %}
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{{- 'Assistant:\n' + content }}
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{%- elif message.role == 'user' %}
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{{- 'User:\n' + content }}
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{%- else %}
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{{- message.role|capitalize + ':\n' + content }}
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{%- endif %}
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{%- if not loop.last %}
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{%- set next_msg_idx = loop.index %}
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{%- if next_msg_idx < messages|length and messages[next_msg_idx].role != 'principle' %}
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{{- '\n\n' }}
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{%- endif %}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{{- '\n[End of Conversation]\n\n' }}
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{{- '[Start of Principle]\n' }}
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{{- principle_ns.principle_content }}
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{{- '\n[End of Principle]\n\n' }}
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{{- 'Your task:\n' }}
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{{- '1. Carefully read the entire conversation.\n' }}
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{{- '2. Judge whether the assistant\'s final response adheres to the principle above.\n' }}
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{{- '3. Think step by step, citing concrete evidence from the conversation.\n' }}
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{{- '4. After your reasoning, output exactly: "Final Judgement: Yes" or "Final Judgement: No".\n\n' }}
|
||||
{{- 'Do NOT output anything after the line that contains the final judgement.' }}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- else %}
|
||||
{# Original template logic for non-principle cases #}
|
||||
{%- if tools %}
|
||||
{{- '<|im_start|>system\n' }}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- messages[0].content + '\n\n' }}
|
||||
{%- endif %}
|
||||
{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||
{%- for tool in tools %}
|
||||
{{- "\n" }}
|
||||
{{- tool | tojson }}
|
||||
{%- endfor %}
|
||||
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||
{%- else %}
|
||||
{%- if messages[0].role == 'system' %}
|
||||
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
||||
{%- for message in messages[::-1] %}
|
||||
{%- set index = (messages|length - 1) - loop.index0 %}
|
||||
{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
|
||||
{%- set ns.multi_step_tool = false %}
|
||||
{%- set ns.last_query_index = index %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- for message in messages %}
|
||||
{%- if message.content is string %}
|
||||
{%- set content = message.content %}
|
||||
{%- else %}
|
||||
{%- set content = '' %}
|
||||
{%- endif %}
|
||||
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
||||
{%- elif message.role == "assistant" %}
|
||||
{%- set reasoning_content = '' %}
|
||||
{%- if message.reasoning_content is string %}
|
||||
{%- set reasoning_content = message.reasoning_content %}
|
||||
{%- else %}
|
||||
{%- if '</think>' in content %}
|
||||
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
||||
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- if loop.index0 > ns.last_query_index %}
|
||||
{%- if loop.last or (not loop.last and reasoning_content) %}
|
||||
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- else %}
|
||||
{{- '<|im_start|>' + message.role + '\n' + content }}
|
||||
{%- endif %}
|
||||
{%- if message.tool_calls %}
|
||||
{%- for tool_call in message.tool_calls %}
|
||||
{%- if (loop.first and content) or (not loop.first) %}
|
||||
{{- '\n' }}
|
||||
{%- endif %}
|
||||
{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
||||
{{- tool_call.name }}
|
||||
{{- '", "arguments": ' }}
|
||||
{%- if tool_call.arguments is string %}
|
||||
{{- tool_call.arguments }}
|
||||
{%- else %}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{%- endif %}
|
||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
|
||||
{{- '\n<tool_response>\n' }}
|
||||
{{- content }}
|
||||
{{- '\n</tool_response>' }}
|
||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|im_start|>assistant\n' }}
|
||||
{%- if enable_thinking is defined and enable_thinking is false %}
|
||||
{{- '<think>\n\n</think>\n\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
|
||||
30
config.json
Normal file
30
config.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 5120,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 25600,
|
||||
"max_position_embeddings": 40960,
|
||||
"max_window_layers": 64,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 64,
|
||||
"num_hidden_layers": 64,
|
||||
"num_key_value_heads": 8,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.51.3",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
9
generation_config.json
Normal file
9
generation_config.json
Normal file
@@ -0,0 +1,9 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"transformers_version": "4.57.0",
|
||||
"do_sample": true,
|
||||
"temperature": 1.0,
|
||||
"top_p": 1.0
|
||||
}
|
||||
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
3
model-00001-of-00014.safetensors
Normal file
3
model-00001-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:77258bd7ad245998402afc96ebb2496cb195ceabdac392ef887ca58530d133d9
|
||||
size 4932307584
|
||||
3
model-00002-of-00014.safetensors
Normal file
3
model-00002-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:884c9e7e9757482f3eedb1ccc87a9832e08973b7c4c70f43f764f5096e22b01b
|
||||
size 4875989696
|
||||
3
model-00003-of-00014.safetensors
Normal file
3
model-00003-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:51bd27fd84dd6622477cb39aeeb6f629d02e06021559cac11be1a256538bc7e2
|
||||
size 4875989720
|
||||
3
model-00004-of-00014.safetensors
Normal file
3
model-00004-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:f0e6f3602e7d515854a623dc78570b5d08831ad8ca23f1bdd3e26ff7c55d4b0f
|
||||
size 4875989752
|
||||
3
model-00005-of-00014.safetensors
Normal file
3
model-00005-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:a9a392e94d34a4f51a39e1fe880f44f1d52d038b7d0c824a058575f3227ba2bf
|
||||
size 4875989752
|
||||
3
model-00006-of-00014.safetensors
Normal file
3
model-00006-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:2d829ac5c8bc7f0274ac5fcb70490c5a5484411f1ab8676ab3df4380f4781c81
|
||||
size 4875989752
|
||||
3
model-00007-of-00014.safetensors
Normal file
3
model-00007-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:a380a3e717490ac178783016132c03aa4ccc89d0ffc433ba57e1a15eb1303bd2
|
||||
size 4875989752
|
||||
3
model-00008-of-00014.safetensors
Normal file
3
model-00008-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:0c7ffb1810ab451479b38faaa2957f6ffc17bf697475adbe870f281c35a39394
|
||||
size 4875989752
|
||||
3
model-00009-of-00014.safetensors
Normal file
3
model-00009-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:2cb6d4f19f289f953e3bd1368c0d67d11a8c4ada3c1b3ff367bacae2ffaf05af
|
||||
size 4875989752
|
||||
3
model-00010-of-00014.safetensors
Normal file
3
model-00010-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:f1a6b687c4c8cedbe9455cbd22e93c24b618c47a154e5b2d8802e6f017c8bb73
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||||
size 4875989752
|
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3
model-00011-of-00014.safetensors
Normal file
3
model-00011-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:d1f7f352c669333fa6df81db8336b598c3df27ecfc408692161b9e547fc022d9
|
||||
size 4875989752
|
||||
3
model-00012-of-00014.safetensors
Normal file
3
model-00012-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:31a0846b29acb3683027ba58d799395c7334e467d1911cf0c9ee0ab37ff3b049
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||||
size 4875989752
|
||||
3
model-00013-of-00014.safetensors
Normal file
3
model-00013-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3cf21a147b547535884842f26707ee43c745cabc15b653fd3c5255e4e509c6cb
|
||||
size 4875989752
|
||||
3
model-00014-of-00014.safetensors
Normal file
3
model-00014-of-00014.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:e87d08957e294d6638693ea3d443af7b91bfa0d95e3c10f9a01d16b7901e7c93
|
||||
size 2080144040
|
||||
715
model.safetensors.index.json
Normal file
715
model.safetensors.index.json
Normal file
@@ -0,0 +1,715 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_parameters": 32762123264,
|
||||
"total_size": 65524246528
|
||||
},
|
||||
"weight_map": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
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|
||||
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|
||||
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|
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|
||||
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||||
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|
||||
}
|
||||
}
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
240
tokenizer_config.json
Normal file
240
tokenizer_config.json
Normal file
File diff suppressed because one or more lines are too long
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user