Instructions to use 0xSero/NousCoder-14B-Tools with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 0xSero/NousCoder-14B-Tools with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="0xSero/NousCoder-14B-Tools")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("0xSero/NousCoder-14B-Tools", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use 0xSero/NousCoder-14B-Tools with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "0xSero/NousCoder-14B-Tools"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "0xSero/NousCoder-14B-Tools",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/0xSero/NousCoder-14B-Tools

SGLang

How to use 0xSero/NousCoder-14B-Tools 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 "0xSero/NousCoder-14B-Tools" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "0xSero/NousCoder-14B-Tools",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "0xSero/NousCoder-14B-Tools" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "0xSero/NousCoder-14B-Tools",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use 0xSero/NousCoder-14B-Tools with Docker Model Runner:
```
docker model run hf.co/0xSero/NousCoder-14B-Tools
```

0xSero commited on Mar 20

Commit

68525b3

verified ·

1 Parent(s): d478dd5

Update model card links and REAP methodology

Browse files

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README.md +13 -0

README.md CHANGED Viewed

@@ -201,3 +201,16 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 ## Support
 If this work is useful, support Sybil Solutions here: [https://donate.sybilsolutions.ai](https://donate.sybilsolutions.ai)

 ## Support
 If this work is useful, support Sybil Solutions here: [https://donate.sybilsolutions.ai](https://donate.sybilsolutions.ai)
+<!-- SERO_MANAGED_TOP_LINKS_START -->
+## Sybil Solutions / 0xSero
+- Donate: [https://donate.sybilsolutions.ai](https://donate.sybilsolutions.ai)
+- REAP paper: [https://arxiv.org/abs/2510.13999](https://arxiv.org/abs/2510.13999)
+- X: [https://x.com/0xsero](https://x.com/0xsero)
+- GitHub: [https://github.com/0xsero](https://github.com/0xsero)
+## Note on REAP methodology
+Some repos in this account are standard fine-tunes, quantizations, or exports rather than REAP-derived MoE variants. For those repos this card only adds the top-level Sybil Solutions / 0xSero links above. REAP methodology details are only attached to the REAP-derived model cards.
+<!-- SERO_MANAGED_TOP_LINKS_END -->