--- title: "BLIP" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0" updated: "2026-11-13" --- # BLIP > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs Salesforce's BLIP vision and language model in a Gradio page, with the training scripts for captioning, retrieval and question answering in the repository. For researchers and developers working with images and text. BLIP is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Salesforce ## About ### What it is This Gradio app from Salesforce runs BLIP, a model that works with both pictures and text. The repository holds the project code, with scripts named for captioning, visual question answering, retrieval and NLVR, plus a sample image. It names the Salesforce/BLIP model and two BERT models from Google. You use it in a browser, or you run a copy on your own computer. ### Who it suits It suits researchers and developers who work with images and text, and students who want to see a vision and language model at work. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | Multimodal researchers | Try BLIP on their own pictures | Open the Space and use the sample image | | Education | Machine learning students | See what a vision and language model can do | Read train\_caption.py next to app.py | | Software | Python developers | Study how the BLIP code and the demo fit together | Download the Space and open app.py | Skip it if you need a light install, because the repository holds 39 files and the model may need a large download. ### Where to use it - A web browser: go to the Space on Hugging Face and try it with no install - Windows, macOS or Linux: run a copy with Python | Use case | Who | What they get back | | --- | --- | --- | | Try BLIP on a picture | Students | The model's output for the image they give | | Compare with your images | Researchers | A quick look at how it handles different pictures | | Read the BLIP code | Developers | Training and evaluation scripts for several tasks | ### How to set it up You need a few things in place first. - Python with pip, on Windows, macOS or Linux - An internet connection to fetch the files from Hugging Face - Spare disk space, since the app names three models and the first run may need extra downloads 1. Install the Hugging Face hub package. 2. Download the Space into a local folder. 3. Move into that folder. 4. Install Gradio 3.0.17 and the packages listed in requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download Salesforce/BLIP --repo-type space --local-dir BLIP cd BLIP pip install gradio==3.0.17 pip install -r requirements.txt python app.py ``` ### How to use it Online, use the Gradio interface the Space page shows. On your own computer, run the main file from the project folder and open the page it serves in your browser. ```sh python app.py ``` ### Example You run python app.py inside the project folder, open the page and give it starrynight.jpeg from the repository. The page returns what the model makes of that picture. ### For newcomers and experts If this is new to you, start online. Go to the Space and try the sample picture before you install anything. A vision and language model reads a picture and works with words about it. If you know the field, note that the repository bundles scripts for pretraining, captioning, retrieval, visual question answering, NLVR and nocaps evaluation. It pins Gradio 3.0.17, an old release, so a fresh environment may need that exact version. Open the Space or run app.py → The Gradio page loads → You give it a picture → The BLIP model processes it → The result appears on the page ### Good to know The source gives no accuracy figures, so test the output on your own pictures before you rely on it. - License: bsd-3-clause - Cost to run: none named, no API key, account or paid service - Data it reaches: the pictures you give it, the files in the repository and the models it names ## README ````markdown # BLIP Runs Salesforce's BLIP vision and language model in a Gradio page, with the training scripts for captioning, retrieval and question answering in the repository. For researchers and developers working with images and text. Made by Salesforce on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This Gradio app from Salesforce runs BLIP, a model that works with both pictures and text. The repository holds the project code, with scripts named for captioning, visual question answering, retrieval and NLVR, plus a sample image. It names the Salesforce/BLIP model and two BERT models from Google. You use it in a browser, or you run a copy on your own computer. Who it suits: It suits researchers and developers who work with images and text, and students who want to see a vision and language model at work. ```table Industry | Who uses it | How they use it | Example Research | Multimodal researchers | Try BLIP on their own pictures | Open the Space and use the sample image Education | Machine learning students | See what a vision and language model can do | Read train_caption.py next to app.py Software | Python developers | Study how the BLIP code and the demo fit together | Download the Space and open app.py ``` Skip it if you need a light install, because the repository holds 39 files and the model may need a large download. Where to use it: - A web browser: go to the Space on Hugging Face and try it with no install - Windows, macOS or Linux: run a copy with Python ```table Use case | Who | What they get back Try BLIP on a picture | Students | The model's output for the image they give Compare with your images | Researchers | A quick look at how it handles different pictures Read the BLIP code | Developers | Training and evaluation scripts for several tasks ``` How to set it up: You need a few things in place first. - Python with pip, on Windows, macOS or Linux - An internet connection to fetch the files from Hugging Face - Spare disk space, since the app names three models and the first run may need extra downloads 1. Install the Hugging Face hub package. 2. Download the Space into a local folder. 3. Move into that folder. 4. Install Gradio 3.0.17 and the packages listed in requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download Salesforce/BLIP --repo-type space --local-dir BLIP cd BLIP pip install gradio==3.0.17 pip install -r requirements.txt python app.py ``` How to use it: Online, use the Gradio interface the Space page shows. On your own computer, run the main file from the project folder and open the page it serves in your browser. ```sh python app.py ``` Example: You run python app.py inside the project folder, open the page and give it starrynight.jpeg from the repository. The page returns what the model makes of that picture. For newcomers and experts: If this is new to you, start online. Go to the Space and try the sample picture before you install anything. A vision and language model reads a picture and works with words about it. If you know the field, note that the repository bundles scripts for pretraining, captioning, retrieval, visual question answering, NLVR and nocaps evaluation. It pins Gradio 3.0.17, an old release, so a fresh environment may need that exact version. ```flow Open the Space or run app.py The Gradio page loads You give it a picture The BLIP model processes it The result appears on the page ``` Good to know: The source gives no accuracy figures, so test the output on your own pictures before you rely on it. - License: bsd-3-clause - Cost to run: none named, no API key, account or paid service - Data it reaches: the pictures you give it, the files in the repository and the models it names ## On Hugging Face, 13 November 2026 - Likes: 431 - Built with: gradio - License: bsd-3-clause ## Links - Space: https://huggingface.co/spaces/Salesforce/BLIP - Files: https://huggingface.co/spaces/Salesforce/BLIP/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [Salesforce/BLIP on Hugging Face](https://huggingface.co/spaces/Salesforce/BLIP) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | BLIP (this page) | 431 | gradio | bsd-3-clause | 2023-03-23 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [VBench Leaderboard](https://mindket.com/p/8841b276-bf55-4c6a-9882-1487225db5de) | 365 | gradio | mit | 2026-04-01 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · johnvanommen · 2026-06-18](https://news.ycombinator.com/item?id=48591007): DeepSeek Introduces Vision: \> Indeed, Gemini really is incredible at image analysis. Yesterday I pointed it at some sloppy handwritten notes and asked it to add up the numbers in the right column, and it did it no problem. I've also used it to find out what TV show or actor is on screen, and various other things. It's quite… - [Bluesky · Steven Dunston · 2026-08-30](https://bsky.app/profile/stevendunston.bsky.social/post/3mudkqnyb4c2k): UncSaaS had a good week. Blip or market shift? Generally, HubSpot seemed more AI forward in its updates over the past few quarters, but the Salesforce partnership with Anthropic gives them some momentum, if the workflows are meaningfully improved. - [Hacker News · salamo · 2024-05-02](https://news.ycombinator.com/item?id=40241101): AI Photo Geolocation: Neat demo. It seems like there may be a few things happening in tandem. I uploaded a picture of a forest and it came back with visually similar images. So the first thing it might be doing is some kind of KNN, and if the pictures have location labels associated applying some sort of weighted… - [Hacker News · simonw · 2023-12-12](https://news.ycombinator.com/item?id=38616639): MemoryCache: Augmenting local AI with browser data: "While there are many OSS for Loading personal data, they dont do images or videos" Local models for images are getting pretty good. LLaVA is an LLM with multi-modal image capabilities that runs pretty well on my laptop: https://simonwillison.net/2023/Nov/29/llamafile/ Models like Salesforce BLIP… - [Hacker News · simonw · 2023-10-26](https://news.ycombinator.com/item?id=38030589): MetaCLIP – Meta AI Research: I suggest trying BLIP for this. I've had really good results from that. https://github.com/salesforce/BLIP I built a tiny Python CLI wrapper for it to make it easier to try: https://github.com/simonw/blip-caption - [Hacker News · kristopolous · 2023-09-27](https://news.ycombinator.com/item?id=37679464): First Impressions with GPT-4V(ision): This actually doesn't seem like it's a giant lift using modern image classifiers. The basic idea is to use diffusion classifiers to caption the image to generate descriptive text and append the prompt. The work part is getting the ensemble right since you'll need to use a general classifier, like… - [Hacker News · minimaxir · 2023-04-28](https://news.ycombinator.com/item?id=35744583): DeepFloyd IF: open-source text-to-image model: For a fast-but-less-robust model, you can use a ViT encode/GPT-2 decoder model: https://huggingface.co/nlpconnect/vit-gpt2-image-captioning For a more-robust-but-hard-to-run model, you can use BLIP2: https://huggingface.co/Salesforce/blip2-opt-2.7b - [Hacker News · xVarunx · 2023-04-23](https://news.ycombinator.com/item?id=35676706): Alpha-Co-Vision: Real-Time Video-To-Text: A real-time video-to-text bot that captures frames generates captions and creates conversational responses using a Large Language Models base to create interactive video descriptions. Powered by Salesforce BLIP (Bootstrapping Language-Image Pre-training) and Cohere AI, this bot is capable of… - [Hacker News · brianjking · 2023-04-15](https://news.ycombinator.com/item?id=35576772): Sam Altman: OpenAI is not training GPT-5 and "won't for some time": The multi-modal vision support? Yes. It's just temporarily available only to BeMyEyes. For now I'm using models like Salesforce/blip2 and OVF and Meta's Segment Anything for visual questioning. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2023-03-23 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Salesforce/BLIP on Hugging Face](https://huggingface.co/spaces/Salesforce/BLIP) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/e5a61c87-6142-4b0e-8f53-32946dad55b0) - [Its page on Mindket](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0)