Text Generation
Transformers
Safetensors
Upper Grand Valley Dani
llama
genomic
text-generation-inference
Instructions to use HuggingFaceBio/Carbon-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceBio/Carbon-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="HuggingFaceBio/Carbon-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("HuggingFaceBio/Carbon-8B") model = AutoModelForCausalLM.from_pretrained("HuggingFaceBio/Carbon-8B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use HuggingFaceBio/Carbon-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HuggingFaceBio/Carbon-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HuggingFaceBio/Carbon-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/HuggingFaceBio/Carbon-8B
- SGLang
How to use HuggingFaceBio/Carbon-8B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "HuggingFaceBio/Carbon-8B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HuggingFaceBio/Carbon-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "HuggingFaceBio/Carbon-8B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HuggingFaceBio/Carbon-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use HuggingFaceBio/Carbon-8B with Docker Model Runner:
docker model run hf.co/HuggingFaceBio/Carbon-8B
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README.md
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Carbon-8B is the 8B-parameter sibling of [Carbon-3B](https://huggingface.co/HuggingFaceBio/Carbon-3B). It is intended for users who can afford additional inference cost in exchange for stronger downstream performance. For the full design rationale, tokenizer specification, evaluation protocol, and usage details, please refer to the **[Carbon-3B model card](https://huggingface.co/HuggingFaceBio/Carbon-3B)** and the Carbon technical report — this card focuses only on what is specific to Carbon-8B.
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## Model Summary
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- **8B-parameter decoder-only autoregressive model** trained on DNA and RNA sequences with a primary focus on eukaryotes.
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Carbon-8B is the 8B-parameter sibling of [Carbon-3B](https://huggingface.co/HuggingFaceBio/Carbon-3B). It is intended for users who can afford additional inference cost in exchange for stronger downstream performance. For the full design rationale, tokenizer specification, evaluation protocol, and usage details, please refer to the **[Carbon-3B model card](https://huggingface.co/HuggingFaceBio/Carbon-3B)** and the Carbon technical report — this card focuses only on what is specific to Carbon-8B.
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- Technical report: https://github.com/huggingface/carbon/blob/main/tech-report.pdf
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- Demo: https://huggingface.co/spaces/HuggingFaceBio/carbon-demo
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## Model Summary
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- **8B-parameter decoder-only autoregressive model** trained on DNA and RNA sequences with a primary focus on eukaryotes.
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