Instructions to use HuggingFaceBio/Carbon-500M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use HuggingFaceBio/Carbon-500M-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="HuggingFaceBio/Carbon-500M-GGUF", filename="carbon-500m-bf16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use HuggingFaceBio/Carbon-500M-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf HuggingFaceBio/Carbon-500M-GGUF:BF16 # Run inference directly in the terminal: llama-cli -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf HuggingFaceBio/Carbon-500M-GGUF:BF16 # Run inference directly in the terminal: llama-cli -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf HuggingFaceBio/Carbon-500M-GGUF:BF16 # Run inference directly in the terminal: ./llama-cli -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf HuggingFaceBio/Carbon-500M-GGUF:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf HuggingFaceBio/Carbon-500M-GGUF:BF16
Use Docker
docker model run hf.co/HuggingFaceBio/Carbon-500M-GGUF:BF16
- LM Studio
- Jan
- Ollama
How to use HuggingFaceBio/Carbon-500M-GGUF with Ollama:
ollama run hf.co/HuggingFaceBio/Carbon-500M-GGUF:BF16
- Unsloth Studio new
How to use HuggingFaceBio/Carbon-500M-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for HuggingFaceBio/Carbon-500M-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for HuggingFaceBio/Carbon-500M-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for HuggingFaceBio/Carbon-500M-GGUF to start chatting
- Docker Model Runner
How to use HuggingFaceBio/Carbon-500M-GGUF with Docker Model Runner:
docker model run hf.co/HuggingFaceBio/Carbon-500M-GGUF:BF16
- Lemonade
How to use HuggingFaceBio/Carbon-500M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull HuggingFaceBio/Carbon-500M-GGUF:BF16
Run and chat with the model
lemonade run user.Carbon-500M-GGUF-BF16
List all available models
lemonade list
File size: 2,021 Bytes
c8ad7cb 673ebdf c8ad7cb 673ebdf c8ad7cb 673ebdf c8ad7cb 4c2888c c8ad7cb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | ---
license: apache-2.0
library_name: gguf
base_model: HuggingFaceBio/Carbon-500M
language:
- dna
tags:
- dna
- genomic
- llama.cpp
- gguf
- hybriddna
---
# Carbon-500M GGUF
GGUF (bf16) conversion of [HuggingFaceBio/Carbon-500M](https://huggingface.co/HuggingFaceBio/Carbon-500M) for use with [llama.cpp](https://github.com/ggml-org/llama.cpp).
Carbon is a hybrid DNA / English language model that switches between Qwen3-4B-Base byte-level BPE for natural text and fixed 6-mer chunking for DNA inside `<dna>...</dna>` tags.
## Requires a recent llama.cpp
HybridDNATokenizer support was merged in [ggml-org/llama.cpp#23410](https://github.com/ggml-org/llama.cpp/pull/23410), so any build from `master` after that works:
```bash
git clone https://github.com/ggml-org/llama.cpp
cd llama.cpp && cmake -B build && cmake --build build -j
```
## Files
| File | Quant | Size |
|---|---|---|
| `carbon-500m-bf16.gguf` | bf16 (lossless from source) | 983 MB |
## Usage
### Download
```bash
hf download HuggingFaceBio/Carbon-500M-GGUF carbon-500m-bf16.gguf --local-dir .
```
### Basic DNA completion
```bash
./build/bin/llama-completion -m carbon-500m-bf16.gguf \
-p '<dna>ATGCGCTAGCTACGATCGATCGTAGCTAGCTAGCTAGCTACG' \
-n 64 --temp 0 -no-cnv
```
### As a draft model for speculative decoding
Carbon-500M shares the HybridDNA vocab with the larger models, so it makes an excellent draft model:
```bash
# 8B target + 500M draft -> ~2x speedup at temp=0
./build/bin/llama-speculative \
-m carbon-8b-bf16.gguf \
-md carbon-500m-bf16.gguf \
-p '<dna>ATGCGCTAGCTACGATCGATCGTAGCTAGCTAGCTAGCTACG' \
-n 256 --temp 0
```
## See also
- Source weights: [HuggingFaceBio/Carbon-500M](https://huggingface.co/HuggingFaceBio/Carbon-500M)
- Other GGUF variants: [500M](https://huggingface.co/HuggingFaceBio/Carbon-500M-GGUF) · [3B](https://huggingface.co/HuggingFaceBio/Carbon-3B-GGUF) · [8B](https://huggingface.co/HuggingFaceBio/Carbon-8B-GGUF)
## License
Apache-2.0, inherited from the source model.
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