Instructions to use Envoid/Cybil-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Envoid/Cybil-13B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Envoid/Cybil-13B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Envoid/Cybil-13B") model = AutoModelForCausalLM.from_pretrained("Envoid/Cybil-13B") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Envoid/Cybil-13B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Envoid/Cybil-13B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Envoid/Cybil-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Envoid/Cybil-13B
- SGLang
How to use Envoid/Cybil-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 "Envoid/Cybil-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": "Envoid/Cybil-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 "Envoid/Cybil-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": "Envoid/Cybil-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Envoid/Cybil-13B with Docker Model Runner:
docker model run hf.co/Envoid/Cybil-13B
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,29 @@
|
|
| 1 |
---
|
| 2 |
license: cc-by-nc-4.0
|
| 3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
---
|
| 2 |
license: cc-by-nc-4.0
|
| 3 |
---
|
| 4 |
+
## Warning: This model may output Adult Content.
|
| 5 |
+
Cybil-13B was created with a series of SLERP merges between
|
| 6 |
+
|
| 7 |
+
Llama-2-13b-chat
|
| 8 |
+
|
| 9 |
+
[sauce1337/BerrySauce-L2-13b](https://huggingface.co/sauce1337/BerrySauce-L2-13b)
|
| 10 |
+
|
| 11 |
+
[Undi95/MLewd-L2-13B-v2-3](https://huggingface.co/Undi95/MLewd-L2-13B-v2-3)
|
| 12 |
+
|
| 13 |
+
[Gryphe/MythoMax-L2-13b](https://huggingface.co/Gryphe/MythoMax-L2-13b)
|
| 14 |
+
|
| 15 |
+
and an unreleased 13B experimental model of mine.
|
| 16 |
+
|
| 17 |
+
The end result seems very stable and excels at any number of general tasks from role play to writing simple python scripts.
|
| 18 |
+
|
| 19 |
+
It responds well to the [Libra-32B SillyTavern format](https://huggingface.co/Envoid/Libra-32B#update-silly-tavern-format) as well as Alpaca Instruct style formatting:
|
| 20 |
+
|
| 21 |
+
I.e.
|
| 22 |
+
|
| 23 |
+
```
|
| 24 |
+
### Instruction:
|
| 25 |
+
Do a thing.
|
| 26 |
+
### Response:
|
| 27 |
+
```
|
| 28 |
+
|
| 29 |
+
Thanks to the Llama-2-chat DNA it does in rare instances produce refusals which can usually just be overcome by regenerating the response.
|