Instructions to use CyberNative/CyberBase-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CyberNative/CyberBase-13b with Transformers:

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

pipe = pipeline("text-generation", model="CyberNative/CyberBase-13b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("CyberNative/CyberBase-13b")
model = AutoModelForCausalLM.from_pretrained("CyberNative/CyberBase-13b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use CyberNative/CyberBase-13b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CyberNative/CyberBase-13b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CyberNative/CyberBase-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/CyberNative/CyberBase-13b

SGLang

How to use CyberNative/CyberBase-13b 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 "CyberNative/CyberBase-13b" \
    --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": "CyberNative/CyberBase-13b",
		"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 "CyberNative/CyberBase-13b" \
        --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": "CyberNative/CyberBase-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use CyberNative/CyberBase-13b with Docker Model Runner:
```
docker model run hf.co/CyberNative/CyberBase-13b
```

CyberNative commited on Aug 18, 2023

Commit

ec9a6fe

1 Parent(s): 6b78b29

Update README.md

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@@ -1,18 +1,17 @@
 ---
 license: llama2
 ---
-!!! THIS IS A PLACEHOLDER !!!
 !!! MODEL COMMING SOON !!!
 # CyberBase 8k - (llama-2-13b - lmsys/vicuna-13b-v1.5-16k)
 Base cybersecurity model for future fine-tuning, it is not reccomended to use on it's own.
-- **CyberBase is a [lmsys/vicuna-13b-v1.5-16k](https://huggingface.co/lmsys/vicuna-13b-v1.5-16k) QLORA fine-tuned on of [CyberNative/github_cybersecurity_READMEs](https://huggingface.co/datasets/CyberNative/github_cybersecurity_READMEs)
-- **sequence_len: 8192
-- **lora_r: 128
-- **lora_alpha: 16
-- **num_epochs: 2
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)

 ---
 license: llama2
 ---
+!!! **THIS IS A PLACEHOLDER** !!!
 !!! MODEL COMMING SOON !!!
 # CyberBase 8k - (llama-2-13b - lmsys/vicuna-13b-v1.5-16k)
 Base cybersecurity model for future fine-tuning, it is not reccomended to use on it's own.
+- **CyberBase** is a [lmsys/vicuna-13b-v1.5-16k](https://huggingface.co/lmsys/vicuna-13b-v1.5-16k) QLORA fine-tuned on [CyberNative/github_cybersecurity_READMEs](https://huggingface.co/datasets/CyberNative/github_cybersecurity_READMEs)
+- **sequence_len:** 8192
+- **lora_r:** 128
+- **lora_alpha:** 16
+- **num_epochs:** 2
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)