Instructions to use appvoid/supertie-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use appvoid/supertie-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/supertie-3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("appvoid/supertie-3") model = AutoModelForCausalLM.from_pretrained("appvoid/supertie-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use appvoid/supertie-3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "appvoid/supertie-3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/supertie-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/appvoid/supertie-3
- SGLang
How to use appvoid/supertie-3 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/supertie-3" \ --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/supertie-3", "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/supertie-3" \ --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/supertie-3", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use appvoid/supertie-3 with Docker Model Runner:
docker model run hf.co/appvoid/supertie-3
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Download README.md from appvoid/supertie-3: direct link, hf CLI and curl.
- Browser
- Download file 1.27 kB
-
https://huggingface.co/appvoid/supertie-3/resolve/main/README.md
- Command line
-
hf download hf://appvoid/supertie-3/README.md
-
curl -L -o README.md https://huggingface.co/appvoid/supertie-3/resolve/main/README.md
1.27 kB
metadata
base_model:
- appvoid/arco-2
- appvoid/ultra-ties-5
- appvoid/arco-x-massive-passthrough-4
library_name: transformers
tags:
- mergekit
- merge
supertie-3
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the DARE TIES merge method using appvoid/arco-x-massive-passthrough-4 as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: appvoid/arco-2
parameters:
density: 0.52
weight: 0.33
- model: appvoid/arco-x-massive-passthrough-4
parameters:
density: 0.52
weight: 0.34
- model: appvoid/ultra-ties-5
parameters:
density: 0.52
weight: 0.33
merge_method: dare_ties
base_model: appvoid/arco-x-massive-passthrough-4
parameters:
normalize: false
int8_mask: true
dtype: float16