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Model: allenai/Llama-3.1-Tulu-3-8B
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README.md

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+---
+license: llama3.1
+language:
+- en
+pipeline_tag: text-generation
+datasets:
+- allenai/RLVR-GSM-MATH-IF-Mixed-Constraints
+base_model:
+- allenai/Llama-3.1-Tulu-3-8B-DPO
+library_name: transformers
+new_version: allenai/Llama-3.1-Tulu-3.1-8B
+model-index:
+- name: Llama-3.1-Tulu-3-8B
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: wis-k/instruction-following-eval
+      split: train
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 82.55
+      name: averaged accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=allenai%2FLlama-3.1-Tulu-3-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: SaylorTwift/bbh
+      split: test
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 16.86
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=allenai%2FLlama-3.1-Tulu-3-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: lighteval/MATH-Hard
+      split: test
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 18.88
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=allenai%2FLlama-3.1-Tulu-3-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      split: train
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 6.26
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=allenai%2FLlama-3.1-Tulu-3-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 10.52
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=allenai%2FLlama-3.1-Tulu-3-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 20.23
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=allenai%2FLlama-3.1-Tulu-3-8B
+      name: Open LLM Leaderboard
+---
+
+<img src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/tulu3/Tulu3-logo.png" alt="Tulu 3 banner" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
+
+# Llama-3.1-Tulu-3-8B
+
+Tülu 3 is a leading instruction following model family, offering a post-training package with fully open-source data, code, and recipes designed to serve as a comprehensive guide for modern techniques.
+This is one step of a bigger process to training fully open-source models, like our [OLMo](https://allenai.org/olmo) models.
+Tülu 3 is designed for state-of-the-art performance on a diversity of tasks in addition to chat, such as MATH, GSM8K, and IFEval.
+
+## Model description
+
+- **Model type:** A model trained on a mix of publicly available, synthetic and human-created datasets.
+- **Language(s) (NLP):** Primarily English
+- **License:** Llama 3.1 Community License Agreement
+- **Finetuned from model:** allenai/Llama-3.1-Tulu-3-8B-DPO
+
+### Model Sources
+
+- **Training Repository:** https://github.com/allenai/open-instruct
+- **Eval Repository:** https://github.com/allenai/olmes
+- **Paper:** https://arxiv.org/abs/2411.15124
+- **Demo:** https://playground.allenai.org/
+
+### Model Family
+
+| **Stage**           | **Llama 3.1 8B**                                                                                          | **Llama 3.1 70B**                                                                                         |
+|----------------------|----------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|
+| **Base Model**       | [meta-llama/Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B)                                | [meta-llama/Llama-3.1-70B](https://huggingface.co/meta-llama/Llama-3.1-70B)                              |
+| **SFT**              | [allenai/Llama-3.1-Tulu-3-8B-SFT](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-SFT)                | [allenai/Llama-3.1-Tulu-3-70B-SFT](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-SFT)              |
+| **DPO**              | [allenai/Llama-3.1-Tulu-3-8B-DPO](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-DPO)                | [allenai/Llama-3.1-Tulu-3-70B-DPO](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B-DPO)              |
+| **Final Models (RLVR)**     | [allenai/Llama-3.1-Tulu-3-8B](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B)                        | [allenai/Llama-3.1-Tulu-3-70B](https://huggingface.co/allenai/Llama-3.1-Tulu-3-70B)                      |
+| **Reward Model (RM)**| [allenai/Llama-3.1-Tulu-3-8B-RM](https://huggingface.co/allenai/Llama-3.1-Tulu-3-8B-RM)                                                     | (Same as 8B)                                                     |
+
+| **Stage** | **Llama 3.1 405B** |
+|-----------|-------------------|
+| **Base Model** | [meta-llama/llama-3.1-405B](https://huggingface.co/meta-llama/llama-3.1-405B) |
+| **SFT** | [allenai/llama-3.1-Tulu-3-405B-SFT](https://huggingface.co/allenai/llama-3.1-Tulu-3-405B-SFT) |
+| **DPO** | [allenai/llama-3.1-Tulu-3-405B-DPO](https://huggingface.co/allenai/llama-3.1-Tulu-3-405B-DPO) |
+| **Final Model (RLVR)** | [allenai/llama-3.1-Tulu-3-405B](https://huggingface.co/allenai/llama-3.1-Tulu-3-405B) |
+| **Reward Model (RM)**| (Same as 8B)
+
+
+## Using the model
+
+### Loading with HuggingFace
+
+To load the model with HuggingFace, use the following snippet:
+```
+from transformers import AutoModelForCausalLM
+
+tulu_model = AutoModelForCausalLM.from_pretrained("allenai/Llama-3.1-Tulu-3-8B")
+```
+
+### VLLM
+
+As a Llama base model, the model can be easily served with:
+```
+vllm serve allenai/Llama-3.1-Tulu-3-8B
+```
+Note that given the long chat template of Llama, you may want to use `--max_model_len=8192`.
+
+### Chat template
+
+The chat template for our models is formatted as:
+```
+<|user|>\nHow are you doing?\n<|assistant|>\nI'm just a computer program, so I don't have feelings, but I'm functioning as expected. How can I assist you today?<|endoftext|>
+```
+Or with new lines expanded:
+```
+<|user|>
+How are you doing?
+<|assistant|>
+I'm just a computer program, so I don't have feelings, but I'm functioning as expected. How can I assist you today?<|endoftext|>
+```
+It is embedded within the tokenizer as well, for `tokenizer.apply_chat_template`.
+
+### System prompt
+
+In Ai2 demos, we use this system prompt by default:
+```
+You are Tulu 3, a helpful and harmless AI Assistant built by the Allen Institute for AI.
+```
+The model has not been trained with a specific system prompt in mind.
+
+### Bias, Risks, and Limitations
+
+The Tülu3 models have limited safety training, but are not deployed automatically with in-the-loop filtering of responses like ChatGPT, so the model can produce problematic outputs (especially when prompted to do so). 
+It is also unknown what the size and composition of the corpus was used to train the base Llama 3.1 models, however it is likely to have included a mix of Web data and technical sources like books and code. 
+See the Falcon 180B model card for an example of this.
+
+
+## Performance
+
+| Benchmark (eval)                | Tülu 3 SFT 8B | Tülu 3 DPO 8B | Tülu 3 8B | Llama 3.1 8B Instruct | Qwen 2.5 7B Instruct | Magpie 8B | Gemma 2 9B Instruct | Ministral 8B Instruct |
+|---------------------------------|----------------|----------------|------------|------------------------|----------------------|-----------|---------------------|-----------------------|
+| **Avg.**                        | 60.4           | 64.4           | **64.8**   | 62.2                  | 57.8                | 44.7      | 55.2               | 58.3                 |
+| **MMLU (0 shot, CoT)**          | 65.9           | 68.7           | 68.2       | 71.2                  | **76.6**            | 62.0      | 74.6               | 68.5                 |
+| **PopQA (15 shot)**             | **29.3**       | 29.3           | 29.1       | 20.2                  | 18.1                | 22.5      | 28.3               | 20.2                 |
+| **TruthfulQA (6 shot)**         | 46.8           | 56.1           | 55.0       | 55.1                  | **63.1**            | 57.0      | 61.4               | 55.5                 |
+| **BigBenchHard (3 shot, CoT)**  | **67.9**       | 65.8           | 66.0       | 62.8                  | 21.7                | 0.9       | 2.5                | 56.2                 |
+| **DROP (3 shot)**               | 61.3           | 62.5           | **62.6**   | 61.5                  | 54.4                | 49.4      | 58.8               | 56.2                 |
+| **MATH (4 shot CoT, Flex)**     | 31.5           | 42.0           | **43.7**   | 42.5                  | 14.8                | 5.1       | 29.8               | 40.0                 |
+| **GSM8K (8 shot, CoT)**         | 76.2           | 84.3           | **87.6**   | 83.4                  | 83.8                | 61.2      | 79.7               | 80.0                 |
+| **HumanEval (pass@10)**         | 86.2           | 83.9           | 83.9       | 86.3                  | **93.1**            | 75.4      | 71.7               | 91.0                 |
+| **HumanEval+ (pass@10)**        | 81.4           | 78.6           | 79.2       | 82.9                  | **89.7**            | 69.1      | 67.0               | 88.5                 |
+| **IFEval (prompt loose)**       | 72.8           | 81.1           | **82.4**   | 80.6                  | 74.7                | 38.8      | 69.9               | 56.4                 |
+| **AlpacaEval 2 (LC % win)**     | 12.4           | 33.5           | 34.5       | 24.2                  | 29.0                | **49.0**  | 43.7               | 31.4                 |
+| **Safety (6 task avg.)**        | **93.1**       | 87.2           | 85.5       | 75.2                  | 75.0                | 46.4      | 75.5               | 56.2                 |
+
+| Benchmark (eval)                | Tülu 3 70B SFT | Tülu 3 DPO 70B | Tülu 3 70B | Llama 3.1 70B Instruct | Qwen 2.5 72B Instruct | Hermes 3 Llama 3.1 70B | Nemotron Llama 3.1 70B |
+|---------------------------------|-----------------|-----------------|-------------|-------------------------|-----------------------|------------------------|-------------------------|
+| **Avg.**                        | 72.6            | 75.9            | **76.0**    | 73.4                   | 71.5                  | 68.3                   | 65.5                   |
+| **MMLU (0 shot, CoT)**          | 78.9            | 83.3            | 83.1        | 85.3                   | **85.5**             | 80.4                   | 83.8                   |
+| **PopQA (15 shot)**             | **48.6**        | 46.3            | 46.5        | 46.4                   | 30.6                  | 48.1                   | 36.4                   |
+| **TruthfulQA (6 shot)**         | 55.7            | 67.9            | 67.6        | 66.8                   | **69.9**             | 66.5                   | 62.6                   |
+| **BigBenchHard (3 shot, CoT)**  | **82.7**        | 81.8            | 82.0        | 73.8                   | 67.2                  | 82.1                   | 0.7                    |
+| **DROP (3 shot)**               | **77.2**        | 74.1            | 74.3        | 77.0                   | 34.2                  | 73.2                   | 68.8                   |
+| **MATH (4 shot CoT, Flex)**     | 53.7            | 62.3            | 63.0        | 56.4                   | **74.3**             | 41.9                   | 55.0                   |
+| **GSM8K (8 shot, CoT)**         | 91.1            | 93.5            | 93.5        | **93.7**              | 89.5                  | 90.0                   | 84.7                   |
+| **HumanEval (pass@10)**         | 92.9            | 92.4            | 92.4        | 93.6                   | 94.0                  | 89.6                   | **94.1**              |
+| **HumanEval+ (pass@10)**        | 87.3            | 88.4            | 88.0        | 89.5                   | **90.8**             | 85.9                   | 85.5                   |
+| **IFEval (prompt loose)**       | 82.1            | 82.6            | 83.2        | **88.0**              | 87.6                  | 76.0                   | 79.9                   |
+| **AlpacaEval 2 (LC % win)**     | 26.3            | 49.6            | 49.8        | 33.4                   | 47.7                  | 28.4                   | **66.1**              |
+| **Safety (6 task avg.)**        | **94.4**        | 89.0            | 88.3        | 76.5                   | 87.0                  | 57.9                   | 69.0                   |
+| Benchmark (eval) | Tülu 3 405B SFT | Tülu 3 405B DPO | Tülu 3 405B | Llama 3.1 405B Instruct | Nous Hermes 3 405B | Deepseek V3 | GPT 4o (11-24) |
+|-----------------|----------------|----------------|-------------|------------------------|-------------------|-------------|----------------|
+| **Avg w/o Safety** | 76.3 | 79.0 | 80.0 | 78.1 | 74.4 | 79.0 | **80.5** |
+| **Avg w/ Safety** | 77.5 | 79.6 | 80.7 | 79.0 | 73.5 | 75.9 | **81.6** |
+| **MMLU (5 shot, CoT)** | 84.4 | 86.6 | 87.0 | **88.0** | 84.9 | 82.1 | 87.9 |
+| **PopQA (3 shot)** | **55.7** | 55.4 | 55.5 | 52.9 | 54.2 | 44.9 | 53.6 |
+| **BigBenchHard (0 shot, CoT)** | 88.0 | 88.8 | 88.6 | 87.1 | 87.7 | **89.5** | 83.3 |
+| **MATH (4 shot, Flex)** | 63.4 | 59.9 | 67.3 | 66.6 | 58.4 | **72.5** | 68.8 |
+| **GSM8K (8 shot, CoT)** | 93.6 | 94.2 | **95.5** | 95.4 | 92.7 | 94.1 | 91.7 |
+| **HumanEval (pass@10)** | 95.7 | **97.2** | 95.9 | 95.9 | 92.3 | 94.6 | 97.0 |
+| **HumanEval+ (pass@10)** | 93.3 | **93.9** | 92.9 | 90.3 | 86.9 | 91.6 | 92.7 |
+| **IFEval (prompt loose)** | 82.4 | 85.0 | 86.0 | **88.4** | 81.9 | 88.0 | 84.8 |
+| **AlpacaEval 2 (LC % win)** | 30.4 | 49.8 | 51.4 | 38.5 | 30.2 | 53.5 | **65.0** |
+| **Safety (6 task avg.)** | 87.7 | 85.5 | 86.7 | 86.8 | 65.8 | 72.2 | **90.9** |
+
+
+## Hyperparamters
+
+PPO settings for RLVR:
+- **Learning Rate**: 3 × 10⁻⁷
+- **Discount Factor (gamma)**: 1.0
+- **General Advantage Estimation (lambda)**: 0.95
+- **Mini-batches (N_mb)**: 1
+- **PPO Update Iterations (K)**: 4
+- **PPO's Clipping Coefficient (epsilon)**: 0.2
+- **Value Function Coefficient (c1)**: 0.1
+- **Gradient Norm Threshold**: 1.0
+- **Learning Rate Schedule**: Linear
+- **Generation Temperature**: 1.0
+- **Batch Size (effective)**: 224
+- **Max Token Length**: 2,048
+- **Max Prompt Token Length**: 2,048
+- **Penalty Reward Value for Responses without an EOS Token**: -10.0
+- **Response Length**: 2,048
+- **Total Episodes**: 100,000
+- **KL penalty coefficient (beta)**: 0.05
+- **Warm up ratio (omega)**: 0.0
+
+## License and use
+
+All Llama 3.1 Tülu3 models are released under Meta's [Llama 3.1 Community License Agreement](https://www.llama.com/llama3_1/license/).
+Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc.
+Tülu3 is intended for research and educational use.
+For more information, please see our [Responsible Use Guidelines](https://allenai.org/responsible-use).
+
+The models have been fine-tuned using a dataset mix with outputs generated from third party models and are subject to additional terms: 
+[Gemma Terms of Use](https://ai.google.dev/gemma/terms) and [Qwen License Agreement](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE) (models were improved using Qwen 2.5).
+
+
+## Citation
+
+If Tülu3 or any of the related materials were helpful to your work, please cite:
+```
+@article{lambert2024tulu3,
+  title = {Tülu 3: Pushing Frontiers in Open Language Model Post-Training},
+  author = {
+    Nathan Lambert and 
+    Jacob Morrison and 
+    Valentina Pyatkin and 
+    Shengyi Huang and 
+    Hamish Ivison and 
+    Faeze Brahman and 
+    Lester James V. Miranda and 
+    Alisa Liu and 
+    Nouha Dziri and 
+    Shane Lyu and 
+    Yuling Gu and 
+    Saumya Malik and 
+    Victoria Graf and 
+    Jena D. Hwang and 
+    Jiangjiang Yang and
+    Ronan Le Bras and
+    Oyvind Tafjord and
+    Chris Wilhelm and
+    Luca Soldaini and 
+    Noah A. Smith and 
+    Yizhong Wang and 
+    Pradeep Dasigi and 
+    Hannaneh Hajishirzi
+  },
+  year = {2024},
+  email = {tulu@allenai.org}
+}
+```
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/allenai__Llama-3.1-Tulu-3-8B-details)!
+Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=allenai%2FLlama-3.1-Tulu-3-8B&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
+
+|      Metric       |Value (%)|
+|-------------------|--------:|
+|**Average**        |    25.88|
+|IFEval (0-Shot)    |    82.55|
+|BBH (3-Shot)       |    16.86|
+|MATH Lvl 5 (4-Shot)|    18.88|
+|GPQA (0-shot)      |     6.26|
+|MuSR (0-shot)      |    10.52|
+|MMLU-PRO (5-shot)  |    20.23|
+

config.json

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+{
+  "_name_or_path": "/model",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.43.4",
+  "use_cache": false,
+  "vocab_size": 128264
+}

configuration.json

@@ -0,0 +1 @@
+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": 128001,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.43.4"
+}

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notice.txt

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+Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved. Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms. Qwen is licensed under the Qwen LICENSE AGREEMENT, Copyright (c) Alibaba Cloud. All Rights Reserved.

special_tokens_map.json

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