Instructions to use Azazelle/Bianca-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azazelle/Bianca-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Azazelle/Bianca-7b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Azazelle/Bianca-7b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Azazelle/Bianca-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Azazelle/Bianca-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Azazelle/Bianca-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Azazelle/Bianca-7b
- SGLang
How to use Azazelle/Bianca-7b 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 "Azazelle/Bianca-7b" \ --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": "Azazelle/Bianca-7b", "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 "Azazelle/Bianca-7b" \ --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": "Azazelle/Bianca-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Azazelle/Bianca-7b with Docker Model Runner:
docker model run hf.co/Azazelle/Bianca-7b
Basic-Sanity
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the rescaled_sample merge method using mistralai/Mistral-7B-v0.1 as a base.
Models Merged
The following models were included in the merge:
- jan-hq/supermario-slerp-v3
- Endevor/InfinityRP-v1-7B
- Nexusflow/Starling-LM-7B-beta
- NeverSleep/Noromaid-7B-0.4-DPO
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Nexusflow/Starling-LM-7B-beta # Reasoning | OpenChat
parameters:
weight: 0.6
density: 0.7
- model: jan-hq/supermario-slerp-v3 # Reasoning | ChatML
parameters:
weight: 0.3
density: 0.5
- model: Endevor/InfinityRP-v1-7B # Roleplay | Alpaca
parameters:
weight: 0.3
density: 0.5
- model: NeverSleep/Noromaid-7B-0.4-DPO # Roleplay | ChatML
parameters:
weight: 0.2
density: 0.4
merge_method: rescaled_sample
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16