Instructions to use appvoid/cloud-7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use appvoid/cloud-7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/cloud-7")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("appvoid/cloud-7") model = AutoModelForCausalLM.from_pretrained("appvoid/cloud-7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use appvoid/cloud-7 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "appvoid/cloud-7" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/cloud-7", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/appvoid/cloud-7
- SGLang
How to use appvoid/cloud-7 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 "appvoid/cloud-7" \ --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": "appvoid/cloud-7", "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 "appvoid/cloud-7" \ --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": "appvoid/cloud-7", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use appvoid/cloud-7 with Docker Model Runner:
docker model run hf.co/appvoid/cloud-7
Download mergekit_config.yml from appvoid/cloud-7: direct link, hf CLI and curl.
- Browser
- Download file 588 Bytes
-
https://huggingface.co/appvoid/cloud-7/resolve/main/mergekit_config.yml
- Command line
-
hf download hf://appvoid/cloud-7/mergekit_config.yml
-
curl -L -o mergekit_config.yml https://huggingface.co/appvoid/cloud-7/resolve/main/mergekit_config.yml
588 Bytes
| merge_method: dare_ties | |
| base_model: MihaiPopa-1/LFM2.5-350M-heretic | |
| dtype: bfloat16 | |
| parameters: | |
| normalize: false | |
| int8_mask: true | |
| models: | |
| # Main complementary skill: terminal / agentic / tool behavior | |
| - model: appvoid/palmer-005-core | |
| parameters: | |
| weight: 0.28 | |
| density: 0.38 | |
| # Assistant tone / conversational instruction-following | |
| - model: squ11z1/claude-oss-350m | |
| parameters: | |
| weight: 0.22 | |
| density: 0.34 | |
| # Generalization / synthetic behavior | |
| - model: mkurman/LiquidAI-LFM2.5-350M-SYNTH | |
| parameters: | |
| weight: 0.14 | |
| density: 0.28 |