Bonsai-27B-GGUF
lmstudio-community · Kit
A GGUF conversion of the 27B Bonsai model for LM Studio, with a 3.80 GB Q1_0 language file and a 0.93 GB BF16 vision projector. Tested for text, vision and par…
Holds GGUF copies of IBM's Granite 4.2 8B model in several quantization levels, ready for llama.cpp. For people who want to run the model locally and read its details from the base model card.
granite-4.2-8b 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 ibm-granite/granite-4.2-8b-GGUF
This repository holds GGUF conversions of IBM's granite-4.2-8b, made in several quantization levels. The model has about 8.8 billion parameters. The files are meant for llama.cpp, which loads GGUF models. The card is short and sends you to the base model's card for the full details.
It suits people who want to run a Granite model on their own computer through llama.cpp, and who are happy to read the base model card for what it can do.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Local AI | Hobbyists | Run an 8.8B model offline with llama.cpp | Chatting with a local model on a desktop |
| Software | App developers | Embed a local Granite model in a tool | A private text assistant inside an app |
| Research | ML researchers | Compare quantization levels of one base model | Checking speed against memory use |
Skip it if you want details on training, languages or benchmarks, since this card leaves those to the base model.
| Use case | Who | What they get back |
|---|---|---|
| Local text generation | Hobbyists | Replies from an 8.8B model on your own machine |
| Quant selection | Developers | A choice of file sizes to fit your memory |
You need these first.
pip install -U huggingface_hub hf download ibm-granite/granite-4.2-8b-GGUF
Load one GGUF file in llama.cpp and send it prompts. This card shows no run command of its own and points to the base model card for its full description.
hf download ibm-granite/granite-4.2-8b-GGUF
Download the files, load one in llama.cpp and send a short prompt. You get generated text back. The card gives no sample prompt or output, so check the base model card for what the model is meant to do.
If you are new, GGUF is a file format that lets llama.cpp run a model on your own computer. Start by downloading the files and reading the base model's card before you pick a size.
If you know the field, these are conversions of an IBM Granite base model into GGUF with several quantization levels. The card gives no benchmarks or per-quant measurements, so test the quant you choose on your own tasks.
Holds GGUF copies of IBM's Granite 4.2 8B model in several quantization levels, ready for llama.cpp. For people who want to run the model locally and read its details from the base model card.
Made by ibm-granite 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 repository holds GGUF conversions of IBM's granite-4.2-8b, made in several quantization levels. The model has about 8.8 billion parameters. The files are meant for llama.cpp, which loads GGUF models. The card is short and sends you to the base model's card for the full details.
Who it suits: It suits people who want to run a Granite model on their own computer through llama.cpp, and who are happy to read the base model card for what it can do.
Industry | Who uses it | How they use it | Example
Local AI | Hobbyists | Run an 8.8B model offline with llama.cpp | Chatting with a local model on a desktop
Software | App developers | Embed a local Granite model in a tool | A private text assistant inside an app
Research | ML researchers | Compare quantization levels of one base model | Checking speed against memory use
Skip it if you want details on training, languages or benchmarks, since this card leaves those to the base model.
Where to use it:
Use case | Who | What they get back
Local text generation | Hobbyists | Replies from an 8.8B model on your own machine
Quant selection | Developers | A choice of file sizes to fit your memory
How to set it up: You need these first.
pip install -U huggingface_hub
hf download ibm-granite/granite-4.2-8b-GGUF
How to use it: Load one GGUF file in llama.cpp and send it prompts. This card shows no run command of its own and points to the base model card for its full description.
hf download ibm-granite/granite-4.2-8b-GGUF
Example: Download the files, load one in llama.cpp and send a short prompt. You get generated text back. The card gives no sample prompt or output, so check the base model card for what the model is meant to do.
For newcomers and experts: If you are new, GGUF is a file format that lets llama.cpp run a model on your own computer. Start by downloading the files and reading the base model's card before you pick a size.
If you know the field, these are conversions of an IBM Granite base model into GGUF with several quantization levels. The card gives no benchmarks or per-quant measurements, so test the quant you choose on your own tasks.
IBM granite-4.2-8b base model
Converted to GGUF
Quantized at several levels
You pick one file
llama.cpp loads it
Good to know:
Download its files with Hugging Face's command line:
pip install -U huggingface_hub
hf download ibm-granite/granite-4.2-8b-GGUF
Then follow the usage in its model card. Nothing in this kit runs by itself.
README.md 4 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 |
|---|---|---|---|---|---|
| granite-4.2-8b GGUF This page | 282,269 | 49 | 8.8B | apache-2.0 | |
| Granite-4.2-3B (GGUF)Shares language · granite-4.2 · gguf | 276,584 | 47 | 3.7B | apache-2.0 | |
| granite-4.1-8b-GGUFShares language · gguf · conversational | 4,426 | 56 | 8.8B | apache-2.0 | |
| granite-4.2-3b-GGUFShares granite-4.2 · gguf · conversational | 6,928 | 9 | 3.7B | apache-2.0 | |
| Granite-4.0-H-350MShares language · conversational | 4,734 | 114 | 340M | apache-2.0 | |
| Granite-4.2-8BShares granite-4.2 · conversational | 61,674 | 120 | 8.8B | apache-2.0 |
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