>>> /Users/geek/Pictures/ollama-hardwriting.jpg what is the content. Added image '/Users/geek/Pictures/ollama-hardwriting.jpg' The image contains a handwritten note in Chinese characters, accompanied by an English translation. The note is divided into three sections:
* **Section 1:** "Ollama" (likely a personal name or title) followed by several Chinese characters. * **Section 2:** A numbered list with the following items: * **Item 1:** "Stay hungry, Stay foolish." (an English phrase) * **Item 2:** A series of Chinese characters * **Item 3:** Another series of Chinese characters
The image appears to be a personal note or message written in Chinese and English.
$ ollama run llama3.2-vision >>> /Users/geek/Pictures/ollama-ocr.png what is the content. Added image '/Users/geek/Pictures/ollama-ocr.png' The image displays a slide from Meta's presentation about Llama 3.2, a large language model developed by Facebook AI Research (FAIR). The slide provides an overview of the model's capabilities and features.
* **Title** + The title of the slide is "Llama 3.2" in large text at the top. * **Description** + Below the title, there is a brief description of Llama 3.2 as a multimodal large language model that can perform
various tasks such as answering questions, generating text, and translating languages. + The description also mentions that Llama 3.2 has been trained on a diverse range of datasets, including but not limited to natural language processing (NLP) tasks like question answering, sentiment analysis, named entity recognition, part-of-speech tagging, dependency parsing, and word sense induction. * **Features** + The slide highlights some key features of Llama 3.2, including its ability to: - Understand and generate human-like language - Perform various NLP tasks with high accuracy - Learn from large amounts of text data - Be fine-tuned for specific applications or domains * **Benefits** + The slide also mentions the benefits of using Llama 3.2, such as: - Improving language understanding and generation capabilities - Enhancing NLP performance in various tasks - Facilitating development of more sophisticated AI systems
Overall, the image provides a concise overview of Llama 3.2's capabilities and features, highlighting its potential applications and benefits in various fields such as natural language processing, computer vision, and robotics.
>>> which language llama3.2 vision support? Llama 3.2 Vision supports the following languages:
* English * German * French * Italian * Portuguese * Hindi * Spanish * Thai
>>> how many size llama3.2 vision has The Llama 3.2-Vision model is available in two sizes: 11B and 90B.
>>> /Users/geek/Pictures/ollama-hist.png what is the most popular value? Added image '/Users/geek/Pictures/ollama-hist.png' The most popular value in this chart is 4, which appears 49 times. This is represented by the tallest bar on the graph.
>>> how many bar in the chart. There are seven bars representing different values from one to seven.
>>> sum the value of bar in the chart To find the sum of the values represented by each bar, we can add up the numbers on the y-axis for each x-axis value.
* Bar 1: 7 * Bar 2: 14 * Bar 3: 28 * Bar 4: 49 * Bar 5: 37 * Bar 6: 17 * Bar 7: 8
Summing these values gives us a total of **160**.
能够理解问题，并结合图标内容给出答案，缺点是不能精确识别图标中的值，需要提高精确度。
图片问答
>>> /Users/geek/Pictures/ollama-cat.webp what is the animal? Unknown command '/Users/geek/Pictures/ollama-cat.webp'. Type /? for help >>> /Users/geek/Pictures/ollama-cat.png what is the animal? Added image '/Users/geek/Pictures/ollama-cat.png' The animals in the image are cats. The cat on the left appears to be a long-haired orange and white domestic shorthair, while the cat on the right seems to be a short-haired brown tabby with a white patch on its chest.
>>> responsd in chinese. (Animals: Two cats)
This image shows two cats. The left one is an orange and white domestic shorthair, while the right one appears to be a short-haired brown tabby with a white patch on its chest.
>>> how many cats in this image? There are 2 cats in this image.
