Instructions to use yvelos/Tsotsallm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yvelos/Tsotsallm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yvelos/Tsotsallm")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("yvelos/Tsotsallm") model = AutoModelForCausalLM.from_pretrained("yvelos/Tsotsallm") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yvelos/Tsotsallm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yvelos/Tsotsallm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yvelos/Tsotsallm", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yvelos/Tsotsallm
- SGLang
How to use yvelos/Tsotsallm 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 "yvelos/Tsotsallm" \ --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": "yvelos/Tsotsallm", "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 "yvelos/Tsotsallm" \ --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": "yvelos/Tsotsallm", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yvelos/Tsotsallm with Docker Model Runner:
docker model run hf.co/yvelos/Tsotsallm
- For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
- Doc / guide: https://huggingface.co/docs/hub/model-cards
- Model Card for TSOTSALLM
- Model Details
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- Model Card Authors [optional]
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For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
Doc / guide: https://huggingface.co/docs/hub/model-cards
{{ card_data }}
Model Card for TSOTSALLM
TSOTSALLM is a large language Model Fine tuning from LLaMA 2 with 7B parameters. This model allow us to annotate automatically TSOTSATable in different task CEA, CTA, CPA ITD.. after annotate wiht use This LLM to generate the composition table.
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