Instructions to use crumb/GLORT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crumb/GLORT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="crumb/GLORT2", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("crumb/GLORT2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use crumb/GLORT2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "crumb/GLORT2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "crumb/GLORT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/crumb/GLORT2
- SGLang
How to use crumb/GLORT2 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 "crumb/GLORT2" \ --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": "crumb/GLORT2", "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 "crumb/GLORT2" \ --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": "crumb/GLORT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use crumb/GLORT2 with Docker Model Runner:
docker model run hf.co/crumb/GLORT2
Update README.md
Browse files
README.md
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| cerebras 111m | 21.550655364990234 | 2.2b |
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| cerebras 256m | 15.203496932983398 | 5.1b |
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| cerebras 590m | 12.098200798034668 | 11.something b |
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| pythia 70m (95.6M) | 22.393400192260742 | 300b |
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| pythia 160m (213M) | 13.933751106262207 | 300b |
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| llama w same settings as cerebras 111m (119m) | 13.882301330566406 | 2.2b |
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| llama plus w same settings as cerebras 111m and llama 70b embeddings (369m) | 13.565109252929688 | 2.2b |
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| **GLORT2 (205m)** | 13.051741600036621 | 2.2b |
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| 13 |
| cerebras 111m | 21.550655364990234 | 2.2b |
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| 14 |
| cerebras 256m | 15.203496932983398 | 5.1b |
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| 15 |
| cerebras 590m | 12.098200798034668 | 11.something b |
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| deduped pythia 70m (95.6M) | 22.393400192260742 | 300b |
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| deduped pythia 160m (213M) | 13.933751106262207 | 300b |
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| deduped pythia 410m (506M) | 9.61842155456543 | 300b |
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| llama w same settings as cerebras 111m (119m) | 13.882301330566406 | 2.2b |
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| 20 |
| llama plus w same settings as cerebras 111m and llama 70b embeddings (369m) | 13.565109252929688 | 2.2b |
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| **GLORT2 (205m)** | 13.051741600036621 | 2.2b |
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