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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("HuggingFaceBio/Carbon-8B") model = AutoModelForCausalLM.from_pretrained("HuggingFaceBio/Carbon-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
Commit History
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Support return_assistant_tokens_mask on slow HybridDNATokenizer for completion-only SFT (apply_chat_template token-boundary mask override)
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Remove base fast-tokenizer files so loads without trust_remote_code raise instead of silently using base BPE
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load chat_template in from_pretrained (vLLM apply_chat_template fix)
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load chat_template in from_pretrained (vLLM apply_chat_template fix)
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load chat_template in from_pretrained (vLLM apply_chat_template fix)
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load chat_template in from_pretrained (vLLM apply_chat_template fix)
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fix convert_tokens_to_string byte-level detok (vLLM)
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Update README.md
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Delete chat_template.jinja
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tokenizer: expose .vocab property for fast-tokenizer-style callers (#1)
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Update README.md
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fix: correct bos/eos/pad token IDs in generation_config (eos=pad=151643, bos=null)
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Upload figures/carbon-8b-banner.png
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update tata and syn
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tokenizer: sync with Carbon-500M/3B (warnings, add_special_tokens pass-through, tolist in decode)
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Initial upload from HuggingFaceBio/carbon-8B-longctx-32k-from-1T-decay@step-227500 with new README
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initial commit
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