Instructions to use appvoid/text-arco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use appvoid/text-arco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/text-arco")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("appvoid/text-arco") model = AutoModelForCausalLM.from_pretrained("appvoid/text-arco") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use appvoid/text-arco with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "appvoid/text-arco" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/text-arco", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/appvoid/text-arco
- SGLang
How to use appvoid/text-arco 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/text-arco" \ --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/text-arco", "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/text-arco" \ --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/text-arco", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use appvoid/text-arco with Docker Model Runner:
docker model run hf.co/appvoid/text-arco
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- merge
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# merge
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This is a
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## Merge Details
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### Merge Method
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This model was merged using the [TIES](https://arxiv.org/abs/2306.01708) merge method using [h2oai/h2o-danube3-500m-base](https://huggingface.co/h2oai/h2o-danube3-500m-base) as a base.
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### Models Merged
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The following models were included in the merge:
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* [appvoid/arco-2](https://huggingface.co/appvoid/arco-2)
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* [appvoid/arco](https://huggingface.co/appvoid/arco)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: appvoid/arco-2
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parameters:
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density: 0.5
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weight: 0.5
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- model: appvoid/arco
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parameters:
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density: 0.5
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weight: 0.5
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merge_method: ties
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base_model: h2oai/h2o-danube3-500m-base
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parameters:
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normalize: true
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int8_mask: true
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dtype: float16
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```
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This is a danube-3-base language model with infused arco models for improved raw language modeling.
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