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--- |
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pipeline_tag: text-generation |
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inference: false |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- language |
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- granite-3.2 |
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- ganite |
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base_model: |
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- ibm-granite/granite-3.2-2b-instruct |
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--- |
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# Granite-3.2-8B-Instruct |
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**Model Summary:** |
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Granite-3.2-8B-Instruct is an 8-billion-parameter, long-context AI model fine-tuned for thinking capabilities. Built on top of [Granite-3.1-8B-Instruct](https://huggingface.co/ibm-granite/granite-3.1-8b-instruct), it has been trained using a mix of permissively licensed open-source datasets and internally generated synthetic data designed for reasoning tasks. The model allows controllability of its thinking capability, ensuring it is applied only when required. |
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- **Developers:** Granite Team, IBM |
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- **Website**: [Granite Docs](https://www.ibm.com/granite/docs/) |
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- **Release Date**: February 26th, 2025 |
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- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0) |
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**Supported Languages:** |
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English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. However, users may finetune this Granite model for languages beyond these 12 languages. |
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**Intended Use:** |
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This model is designed to handle general instruction-following tasks and can be integrated into AI assistants across various domains, including business applications. |
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**Capabilities** |
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* **Thinking** |
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* Summarization |
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* Text classification |
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* Text extraction |
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* Question-answering |
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* Retrieval Augmented Generation (RAG) |
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* Code related tasks |
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* Function-calling tasks |
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* Multilingual dialog use cases |
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* Long-context tasks including long document/meeting summarization, long document QA, etc. |
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**Generation:** |
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This is a simple example of how to use Granite-3.2-8B-Instruct model. |
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Install the following libraries: |
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```shell |
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pip install torch torchvision torchaudio |
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pip install accelerate |
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pip install transformers |
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``` |
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Then, copy the snippet from the section that is relevant for your use case. |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed |
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import torch |
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model_path="ibm-granite/granite-3.2-8b-instruct" |
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device="cuda" |
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model = AutoModelForCausalLM.from_pretrained( |
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model_path, |
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device_map=device, |
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torch_dtype=torch.bfloat16, |
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) |
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tokenizer = AutoTokenizer.from_pretrained( |
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model_path |
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) |
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conv = [{"role": "user", "content":"You have 10 liters of a 30% acid solution. How many liters of a 70% acid solution must be added to achieve a 50% acid mixture?"}] |
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input_ids = tokenizer.apply_chat_template(conv, return_tensors="pt", thinking=True, return_dict=True, add_generation_prompt=True).to(device) |
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set_seed(42) |
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output = model.generate( |
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**input_ids, |
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max_new_tokens=8192, |
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) |
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prediction = tokenizer.decode(output[0, input_ids["input_ids"].shape[1]:], skip_special_tokens=True) |
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print(prediction) |
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``` |
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**Example Outputs** |
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- thinking=True |
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```md |
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Here is my thought process: |
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1. We know we start with 10 liters of a 30% acid solution, so there's 3 liters of pure acid in it (10 liters * 0.3). |
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2. We need to determine how much of the 70% acid solution to add such that the final mixture is 50% acid. |
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3. Let's say x liters of the 70% acid solution are added. This will contribute 0.7x liters of pure acid. |
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4. The total volume of the new mixture will be 10 + x liters, and the total amount of pure acid will be 3 + 0.7x liters. |
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5. We need to set up an equation where (3 + 0.7x) / (10 + x) = 0.5 (since we want a 50% acid mixture). |
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6. Solving this equation for x will give us the volume of 70% solution needed. |
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Here is my response: |
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To solve this, we need to set up an equation based on the concentration of acid before and after mixing. |
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1. **Initial Acid Content**: |
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- We start with 10 liters of a 30% acid solution. |
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- Pure acid in this = 10 * 0.3 = 3 liters. |
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2. **Variable for Addition**: |
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- Let x be the liters of 70% acid solution to be added. |
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- Pure acid in x liters of 70% solution = 0.7x liters. |
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3. **Final Mixture Concentration**: |
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- Total volume of mixture = 10 + x liters. |
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- Total pure acid in the mixture = 3 (from initial solution) + 0.7x (from added solution). |
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4. **Setting up the equation for 50% acid concentration**: |
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- We require that the ratio of pure acid to total volume is 0.5 (50%). |
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- Therefore, the equation is: |
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\[ |
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\frac{3 + 0.7x}{10 + x} = 0.5 |
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\] |
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5. **Solving the equation**: |
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Multiply both sides by (10 + x) to clear the fraction: |
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\[ |
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3 + 0.7x = 0.5(10 + x) |
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\] |
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Expanding the right side: |
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\[ |
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3 + 0.7x = 5 + 0.5x |
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\] |
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Subtract 0.5x from both sides: |
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\[ |
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3 + 0.2x = 5 |
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\] |
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Subtract 3 from both sides: |
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\[ |
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0.2x = 2 |
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\] |
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Divide by 0.2: |
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\[ |
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x = 10 |
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\] |
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So, 10 liters of the 70% acid solution must be added to the initial 10 liters of 30% solution to get a 50% acid mixture. |
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Let's verify: |
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- Initial acid: 3 liters |
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- Acid from added solution: 0.7 * 10 = 7 liters |
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- Total acid: 3 + 7 = 10 liters |
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- Total volume: 10 + 10 = 20 liters |
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- Acid percentage: \(\frac{10}{20} = 0.5 = 50\%\) |
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This confirms our solution. |
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Final answer: 10 liters of 70% acid solution should be added. |
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``` |
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- thinking=False |
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```md |
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Let's denote the amount of 70% acid solution to be added as x liters. |
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We start with 10 liters of a 30% acid solution, which means there are 0.3 * 10 = 3 liters of pure acid in it. |
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We want to end up with a 50% acid solution after adding x liters of 70% acid solution. The total volume of the mixture will be 10 + x liters, and we want half of this volume to be pure acid. |
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So, the amount of pure acid in the final mixture should be 0.5 * (10 + x) liters. |
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The amount of pure acid in the final mixture comes from two sources: the original 30% solution and the added 70% solution. So, we can set up the following equation: |
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3 (from the original solution) + 0.7x (from the added solution) = 0.5 * (10 + x) |
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Now, let's solve for x: |
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3 + 0.7x = 5 + 0.5x |
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0.7x - 0.5x = 5 - 3 |
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0.2x = 2 |
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x = 2 / 0.2 |
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x = 10 |
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So, you need to add 10 liters of a 70% acid solution to the 10 liters of a 30% acid solution to get a 50% acid mixture. |
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``` |
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**Evaluation Results:** |
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<table> |
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<thead> |
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<tr> |
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<th style="text-align:left; background-color: #001d6c; color: white;">Models</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">ArenaHard</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">Alpaca-Eval-2</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">MMLU</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">PopQA</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">TruthfulQA</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">BigBenchHard</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">DROP</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">GSM8K</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">HumanEval</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">HumanEval+</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">IFEval</th> |
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<th style="text-align:center; background-color: #001d6c; color: white;">AttaQ</th> |
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</tr></thead> |
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<tbody> |
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<tr> |
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<td style="text-align:left; background-color: #DAE8FF; color: black;">Llama-3.1-8B-Instruct</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">36.43</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">27.22</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">69.15</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">28.79</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">52.79</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">72.66</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">61.48</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">83.24</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">85.32</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">80.15</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">79.10</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">83.43</td> |
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</tr> |
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<tr> |
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<td style="text-align:left; background-color: #DAE8FF; color: black;">DeepSeek-R1-Distill-Llama-8B</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">17.17</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">21.85</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">45.80</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">13.25</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">47.43</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">65.71</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">44.46</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">72.18</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">67.54</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">62.91</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">66.50</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">42.87</td> |
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</tr> |
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<tr> |
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<td style="text-align:left; background-color: #DAE8FF; color: black;">Qwen-2.5-7B-Instruct</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">25.44</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">30.34</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">74.30</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">18.12</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">63.06</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">70.40</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">54.71</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">84.46</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">93.35</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">89.91</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">74.90</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">81.90</td> |
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</tr> |
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<tr> |
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<td style="text-align:left; background-color: #DAE8FF; color: black;">DeepSeek-R1-Distill-Qwen-7B</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">10.36</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">15.35</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">50.72</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">9.94</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">47.14</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">65.04</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">42.76</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">78.47</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">79.89</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">78.43</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">59.10</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">42.45</td> |
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</tr> |
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<tr> |
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<td style="text-align:left; background-color: #DAE8FF; color: black;">Granite-3.1-8B-Instruct</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">37.58</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">30.34</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">66.77</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">28.7</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">65.84</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">68.55</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">50.78</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">79.15</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">89.63</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">85.79</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">73.20</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">85.73</td> |
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</tr> |
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<tr> |
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<td style="text-align:left; background-color: #DAE8FF; color: black;">Granite-3.1-2B-Instruct</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">23.3</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">27.17</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">57.11</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">20.55</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">59.79</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">54.46</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">18.68</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">67.55</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">79.45</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">75.26</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">63.59</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">84.7</td> |
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</tr> |
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<tr> |
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<td style="text-align:left; background-color: #DAE8FF; color: black;">Granite-3.2-2B-Instruct</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">24.86</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">34.51</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">57.18</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">20.56</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">59.8</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">52.27</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">21.12</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">67.02</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">80.13</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">73.39</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">61.55</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">83.23</td> |
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</tr> |
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<tr> |
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<td style="text-align:left; background-color: #DAE8FF; color: black;"><b>Granite-3.2-8B-Instruct</b></td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">55.25</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">61.19</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">66.79</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">28.04</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">66.92</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">64.77</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">50.95</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">81.65</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">89.35</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">85.72</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">74.31</td> |
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<td style="text-align:center; background-color: #DAE8FF; color: black;">85.42</td> |
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</tr> |
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</tbody></table> |
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**Training Data:** |
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Overall, our training data is largely comprised of two key sources: (1) publicly available datasets with permissive license, (2) internal synthetically generated data targeted to enhance reasoning capabilites. |
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<!-- A detailed attribution of datasets can be found in [Granite 3.2 Technical Report (coming soon)](#), and [Accompanying Author List](https://github.com/ibm-granite/granite-3.0-language-models/blob/main/author-ack.pdf). --> |
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**Infrastructure:** |
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We train Granite-3.2-8B-Instruct using IBM's super computing cluster, Blue Vela, which is outfitted with NVIDIA H100 GPUs. This cluster provides a scalable and efficient infrastructure for training our models over thousands of GPUs. |
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**Ethical Considerations and Limitations:** |
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Granite-3.2-8B-Instruct builds upon Granite-3.1-8B-Instruct, leveraging both permissively licensed open-source and select proprietary data for enhanced performance. Since it inherits its foundation from the previous model, all ethical considerations and limitations applicable to [Granite-3.1-8B-Instruct](https://huggingface.co/ibm-granite/granite-3.1-8b-instruct) remain relevant. |
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**Resources** |
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- ⭐️ Learn about the latest updates with Granite: https://www.ibm.com/granite |
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- 📄 Get started with tutorials, best practices, and prompt engineering advice: https://www.ibm.com/granite/docs/ |
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- 💡 Learn about the latest Granite learning resources: https://ibm.biz/granite-learning-resources |
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<!-- ## Citation |
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``` |
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@misc{granite-models, |
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author = {author 1, author2, ...}, |
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title = {}, |
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journal = {}, |
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volume = {}, |
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year = {2024}, |
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url = {https://arxiv.org/abs/0000.00000}, |
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} |
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``` --> |
