Huashu Design
alchaincyf · Skill
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Reads images and text and answers in text, as a small GGUF copy of Qwen3.5-2B by unsloth. Meant for local prototyping, fine-tuning and research.
Qwen3.5-2B-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.
pip install -U huggingface_hub hf download unsloth/Qwen3.5-2B-GGUF
This is a GGUF copy of Qwen3.5-2B, made by unsloth. The model has 1.9B parameters and takes an image plus text, then answers in text. Hugging Face estimates the files at about 941 MB at 4-bit, which is small next to larger models.
Developers and researchers who want a small model for prototyping, fine-tuning on one task, or other research work. The original card names those as its intended uses.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Software | Developers | Prototype an app that reads images and text on a local machine | Try a picture-and-question flow before choosing a larger model |
| Research | Researchers | Study how a small multimodal model behaves | Compare answers from this copy with its base model |
| Education | Students and teachers | Learn how a local model is downloaded and loaded | Fetch the files, load them and ask one short question |
| Machine learning | Fine-tuners | Start a narrow, single-task fine-tune from a small base | Adapt it to sort a set of images into labels |
Skip it if you need the best answers on hard tasks, because its size points to testing and experiments rather than heavy work.
| Use case | Who | What they get back |
|---|---|---|
| Image question | Developers | A text answer about a picture you attach |
| Plain text chat | Hobbyists | A short text reply from a small model |
| Base for tuning | Researchers | A small starting point for one narrow task |
You need a computer with Python and pip, plus a program that can open GGUF files.
pip install -U huggingface_hub hf download unsloth/Qwen3.5-2B-GGUF
Run the download command once, then point your GGUF program at the saved file and send it a picture with a question. The card links an Unsloth guide on running Qwen3.5 locally, and that guide holds the run steps.
| Tool | What it does |
|---|---|
| pip | Installs or updates the library that fetches model files |
| hf download | Fetches a repository by name and saves its files on your computer |
You attach a photo of a street sign and ask, "What does this sign say?" The model reads the image and replies in plain text. With a model this small, check the answer yourself before relying on it.
If you are new to this, think of the file as a compact assistant that lives on your own computer and can look at a picture. Start by downloading it with the two commands above, then ask it one simple question about one image.
If you work with models, note the base design. The card lists 24 layers that alternate Gated DeltaNet blocks with gated attention blocks, a vision encoder, tied output embeddings and a native context of 262,144 tokens. It also claims coverage of 201 languages. Quantizing to 4-bit generally trades some accuracy for a much smaller file.
Reads images and text and answers in text, as a small GGUF copy of Qwen3.5-2B by unsloth. Meant for local prototyping, fine-tuning and research.
Made by unsloth on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.
What it is: This is a GGUF copy of Qwen3.5-2B, made by unsloth. The model has 1.9B parameters and takes an image plus text, then answers in text. Hugging Face estimates the files at about 941 MB at 4-bit, which is small next to larger models.
Who it suits: Developers and researchers who want a small model for prototyping, fine-tuning on one task, or other research work. The original card names those as its intended uses.
Title: Who uses it
Industry | Who uses it | How they use it | Example
Software | Developers | Prototype an app that reads images and text on a local machine | Try a picture-and-question flow before choosing a larger model
Research | Researchers | Study how a small multimodal model behaves | Compare answers from this copy with its base model
Education | Students and teachers | Learn how a local model is downloaded and loaded | Fetch the files, load them and ask one short question
Machine learning | Fine-tuners | Start a narrow, single-task fine-tune from a small base | Adapt it to sort a set of images into labels
Skip it if you need the best answers on hard tasks, because its size points to testing and experiments rather than heavy work.
Where to use it:
Title: What it is used for
Use case | Who | What they get back
Image question | Developers | A text answer about a picture you attach
Plain text chat | Hobbyists | A short text reply from a small model
Base for tuning | Researchers | A small starting point for one narrow task
How to set it up: You need a computer with Python and pip, plus a program that can open GGUF files.
pip install -U huggingface_hub
hf download unsloth/Qwen3.5-2B-GGUF
How to use it: Run the download command once, then point your GGUF program at the saved file and send it a picture with a question. The card links an Unsloth guide on running Qwen3.5 locally, and that guide holds the run steps.
Tool | What it does
pip | Installs or updates the library that fetches model files
hf download | Fetches a repository by name and saves its files on your computer
Example: You attach a photo of a street sign and ask, "What does this sign say?" The model reads the image and replies in plain text. With a model this small, check the answer yourself before relying on it.
For newcomers and experts: If you are new to this, think of the file as a compact assistant that lives on your own computer and can look at a picture. Start by downloading it with the two commands above, then ask it one simple question about one image.
If you work with models, note the base design. The card lists 24 layers that alternate Gated DeltaNet blocks with gated attention blocks, a vision encoder, tied output embeddings and a native context of 262,144 tokens. It also claims coverage of 201 languages. Quantizing to 4-bit generally trades some accuracy for a much smaller file.
Download the GGUF files
Open them in a GGUF-capable program
Send an image and a question
Read the text answer
Good to know:
Download its files with Hugging Face's command line:
pip install -U huggingface_hub
hf download unsloth/Qwen3.5-2B-GGUF
Then follow the usage in its model card. Nothing in this kit runs by itself.
README.md 5 KB
Listed Hugging Face models in the same category that share the most tags with this one.
| Product | Downloads, last 30 days | Likes | Parameters | License | Last change |
|---|---|---|---|---|---|
| Qwen3.5-2B-GGUF This page | 505,712 | 176 | 1.9B | apache-2.0 | |
| Qwen3.6-35B-A3B-MTP-GGUFShares unsloth · image-text-to-text · gguf | 2,315,167 | 1,051 | 35.5B | apache-2.0 | |
| Qwen3.5-9B-GGUFShares unsloth · image-text-to-text · gguf | 1,969,901 | 1,074 | 9B | apache-2.0 | |
| Qwen3.6-35B-A3B-GGUFShares unsloth · image-text-to-text · gguf | 1,649,871 | 1,789 | 34.7B | apache-2.0 | |
| Qwen3.5-4B-GGUFShares unsloth · image-text-to-text · gguf | 1,537,690 | 557 | 4.2B | apache-2.0 | |
| Qwopus3.8-27B-Flash-V2-GGUFShares unsloth · image-text-to-text · gguf | 897,675 | 75 | 461M | apache-2.0 |
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