Instructions to use tangledgroup/tangled-alpha-0.11-core with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tangledgroup/tangled-alpha-0.11-core with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tangledgroup/tangled-alpha-0.11-core")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tangledgroup/tangled-alpha-0.11-core", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use tangledgroup/tangled-alpha-0.11-core with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tangledgroup/tangled-alpha-0.11-core" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tangledgroup/tangled-alpha-0.11-core", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tangledgroup/tangled-alpha-0.11-core
- SGLang
How to use tangledgroup/tangled-alpha-0.11-core 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 "tangledgroup/tangled-alpha-0.11-core" \ --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": "tangledgroup/tangled-alpha-0.11-core", "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 "tangledgroup/tangled-alpha-0.11-core" \ --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": "tangledgroup/tangled-alpha-0.11-core", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tangledgroup/tangled-alpha-0.11-core with Docker Model Runner:
docker model run hf.co/tangledgroup/tangled-alpha-0.11-core
Commit History
eval pretrain-core-3; 79c51bc
eval pretrain-core-3 c0f6e02
Marko Tasic commited on
pretrain core 3 a67e190
Marko Tasic commited on
Merge branch 'main' of hf.co:tangledgroup/tangled-alpha-0.11-core 701ae11
Marko Tasic commited on
pretrain core 2 508cb73
Marko Tasic commited on
pretrain_core_model_3 964f6ac
pretrain_core_model_2 5196aad
pretrain_core_model_2 f79c95e
out/pretrain-core-1/final 4d6c833
Marko Tasic commited on
out/pretrain-core-1/final c3d4e9e
Marko Tasic commited on
Merge branch 'main' of hf.co:tangledgroup/tangled-alpha-0.11-core a71ecdf
pretrain core 1 fc621f2
Merge branch 'main' of hf.co:tangledgroup/tangled-alpha-0.11-core 2da6f84
Marko Tasic commited on
pretrain-core-0/checkpoint 1251039
Marko Tasic commited on
pretrain_core_model_1 374df08
eval 98b9040
Merge branch 'main' of hf.co:tangledgroup/tangled-alpha-0.11-core f6d87b1
eval c2bf67d
evaluate 6935d17
Marko Tasic commited on
Merge branch 'main' of hf.co:tangledgroup/tangled-alpha-0.11-core fcbe680
Marko Tasic commited on
pretrain out final 98aa671
Marko Tasic commited on