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ibm-granite
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Model Details
Model Provider
ibm-granite
Model Tree
ibm-granite/granite-3.1-2b-instruct
Input Modalities
Output Modalities
Supported Functionality
Model Summary: Granite-3.2-2B-Instruct is an 2-billion-parameter, long-context AI model fine-tuned for thinking capabilities. Built on top of Granite-3.1-2B-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.
Supported Languages: 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.
Intended Use: This model is designed to handle general instruction-following tasks and can be integrated into AI assistants across various domains, including business applications.
Capabilities
Generation: This is a simple example of how to use Granite-3.2-2B-Instruct model.
Install the following libraries:
shell
pip install torch torchvision torchaudiopip install acceleratepip install transformersThen, copy the snippet from the section that is relevant for your use case.
python
from transformers import AutoModelForCausalLM, AutoTokenizer, set_seedimport torch model_path="ibm-granite/granite-3.2-2b-instruct"device="cuda"model = AutoModelForCausalLM.from_pretrained( model_path, device_map=device, torch_dtype=torch.bfloat16, )tokenizer = AutoTokenizer.from_pretrained( model_path) 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?"}] input_ids = tokenizer.apply_chat_template(conv, return_tensors="pt", thinking=True, return_dict=True, add_generation_prompt=True).to(device) set_seed(42)output = model.generate( **input_ids, max_new_tokens=8192,) prediction = tokenizer.decode(output[0, input_ids["input_ids"].shape[1]:], skip_special_tokens=True)print(prediction)Example Outputs
md
Here is my thought process: 1. First, let's understand the composition of the initial 10 liters of 30% acid solution: - Acid content = 30% of 10 liters = 0.30 * 10 = 3 liters 2. We want to end up with a 50% acid solution. Let's denote the volume of the 70% acid solution to be added as 'x' liters. 3. The amount of acid in the final mixture (50% solution) should equal the initial acid content plus the acid from the added 70% solution. - Total acid in final mixture = 0.50 * (10 + x) 4. The equation representing the total acid content is: 3 (from initial solution) + 0.70 * x (from added solution) = 0.50 * (10 + x) 5. Now, we solve for 'x': 3 + 0.70x = 5 + 0.50x 0.70x - 0.50x = 5 - 3 0.20x = 2 x = 2 / 0.20 x = 10 liters 6. Therefore, 10 liters of a 70% acid solution must be added to the initial 10 liters of 30% acid solution to achieve a 50% acid mixture. Here is my response: To solve this problem, we need to determine how much of a 70% acid solution must be added to a 10-liter solution that is already 30% acid to create a new mixture that is 50% acid. Here's how to calculate it: 1. **Initial Acid Content**: - The initial 10-liter solution contains 3 liters of acid (since 30% of 10 liters). 2. **Desired Final Acid Content**: - We want the final mixture to be 50% acid. 3. **Equation Setup**: - Let 'x' be the volume (in liters) of the 70% acid solution to be added. - The equation representing the total acid content in the final mixture (which is 10 liters from the initial solution plus 'x' liters of the added solution) should equal 50% of the total volume (10 + x). - This gives us: 3 (acid from initial solution) + 0.70x (acid from added solution) = 0.50(10 + x) 4. **Solving the Equation**: - First, simplify the right side of the equation: 0.50(10 + x) = 5 + 0.50x - Now, the equation is: 3 + 0.70x = 5 + 0.50x - Subtract 0.50x from both sides: 0.20x = 2 - Divide both sides by 0.20: x = 2 / 0.20 - x = 10 liters 5. **Conclusion**: - To achieve a 50% acid mixture from the initial 30% solution, you need to add 10 liters of a 70% acid solution. So, the final answer is that 10 liters of a 70% acid solution must be added to the initial 10 liters of 30% acid solution.md
To solve this problem, we'll use the concept of volume and concentration. Let's denote the amount of 70% acid solution we need to add as "x" liters. First, let's find out how much acid is in the initial 10-liter solution: Acid in initial solution = 30% of 10 liters = 0.30 * 10 = 3 liters Now, we want to end up with a 50% acid solution in a total volume of (10 + x) liters. Let's denote the final volume as V. Final acid concentration = 50%Final acid amount = 50% of V = 0.50 * V We know the initial acid amount and the final acid amount, so we can set up an equation: Initial acid amount + Acid from added solution = Final acid amount3 liters + (70% of x) = 0.50 * (10 + x) Now, let's solve for x: 0.70x + 3 = 0.50 * 10 + 0.50x0.70x - 0.50x = 0.50 * 10 - 30.20x = 5 - 30.20x = 2x = 2 / 0.20x = 10 liters So, you need to add 10 liters of a 70% acid solution to the initial 10-liter 30% acid solution to achieve a 50% acid mixture.Evaluation Results:
Training Data: 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.
Infrastructure: We train Granite-3.2-2B-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.
Ethical Considerations and Limitations: Granite-3.2-2B-Instruct builds upon Granite-3.1-2B-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-3.1-2B-Instruct remain relevant.
Resources
from transformers import AutoModelForCausalLM, AutoTokenizer, set_seedimport torch model_path="ibm-granite/granite-3.2-2b-instruct"device="cuda"model = AutoModelForCausalLM.from_pretrained( model_path, device_map=device, torch_dtype=torch.bfloat16, )tokenizer = AutoTokenizer.from_pretrained( model_path) 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?"}] input_ids = tokenizer.apply_chat_template(conv, return_tensors="pt", thinking=True, return_dict=True, add_generation_prompt=True).to(device) set_seed(42)output = model.generate( **input_ids, max_new_tokens=8192,) prediction = tokenizer.decode(output[0, input_ids["input_ids"].shape[1]:], skip_special_tokens=True)print(prediction)pip install torch torchvision torchaudiopip install acceleratepip install transformersHere is my thought process: 1. First, let's understand the composition of the initial 10 liters of 30% acid solution: - Acid content = 30% of 10 liters = 0.30 * 10 = 3 liters 2. We want to end up with a 50% acid solution. Let's denote the volume of the 70% acid solution to be added as 'x' liters. 3. The amount of acid in the final mixture (50% solution) should equal the initial acid content plus the acid from the added 70% solution. - Total acid in final mixture = 0.50 * (10 + x) 4. The equation representing the total acid content is: 3 (from initial solution) + 0.70 * x (from added solution) = 0.50 * (10 + x) 5. Now, we solve for 'x': 3 + 0.70x = 5 + 0.50x 0.70x - 0.50x = 5 - 3 0.20x = 2 x = 2 / 0.20 x = 10 liters 6. Therefore, 10 liters of a 70% acid solution must be added to the initial 10 liters of 30% acid solution to achieve a 50% acid mixture. Here is my response: To solve this problem, we need to determine how much of a 70% acid solution must be added to a 10-liter solution that is already 30% acid to create a new mixture that is 50% acid. Here's how to calculate it: 1. **Initial Acid Content**: - The initial 10-liter solution contains 3 liters of acid (since 30% of 10 liters). 2. **Desired Final Acid Content**: - We want the final mixture to be 50% acid. 3. **Equation Setup**: - Let 'x' be the volume (in liters) of the 70% acid solution to be added. - The equation representing the total acid content in the final mixture (which is 10 liters from the initial solution plus 'x' liters of the added solution) should equal 50% of the total volume (10 + x). - This gives us: 3 (acid from initial solution) + 0.70x (acid from added solution) = 0.50(10 + x) 4. **Solving the Equation**: - First, simplify the right side of the equation: 0.50(10 + x) = 5 + 0.50x - Now, the equation is: 3 + 0.70x = 5 + 0.50x - Subtract 0.50x from both sides: 0.20x = 2 - Divide both sides by 0.20: x = 2 / 0.20 - x = 10 liters 5. **Conclusion**: - To achieve a 50% acid mixture from the initial 30% solution, you need to add 10 liters of a 70% acid solution. So, the final answer is that 10 liters of a 70% acid solution must be added to the initial 10 liters of 30% acid solution.To solve this problem, we'll use the concept of volume and concentration. Let's denote the amount of 70% acid solution we need to add as "x" liters. First, let's find out how much acid is in the initial 10-liter solution: Acid in initial solution = 30% of 10 liters = 0.30 * 10 = 3 liters Now, we want to end up with a 50% acid solution in a total volume of (10 + x) liters. Let's denote the final volume as V. Final acid concentration = 50%Final acid amount = 50% of V = 0.50 * V We know the initial acid amount and the final acid amount, so we can set up an equation: Initial acid amount + Acid from added solution = Final acid amount3 liters + (70% of x) = 0.50 * (10 + x) Now, let's solve for x: 0.70x + 3 = 0.50 * 10 + 0.50x0.70x - 0.50x = 0.50 * 10 - 30.20x = 5 - 30.20x = 2x = 2 / 0.20x = 10 liters So, you need to add 10 liters of a 70% acid solution to the initial 10-liter 30% acid solution to achieve a 50% acid mixture.