Instructions to use HuggingFaceBio/Carbon-500M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

Carbon-500M-GGUF / README.md

kashif HF Staff

card: HybridDNATokenizer merged upstream (#23410)

673ebdf verified 1 day ago

preview code

raw

history blame contribute delete

2.02 kB

	---
	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.