Instructions to use appvoid/cortex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use appvoid/cortex with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/cortex", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("appvoid/cortex", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use appvoid/cortex with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "appvoid/cortex" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/cortex", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/appvoid/cortex
- SGLang
How to use appvoid/cortex 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/cortex" \ --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/cortex", "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/cortex" \ --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/cortex", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use appvoid/cortex with Docker Model Runner:
docker model run hf.co/appvoid/cortex
unified-v1-ouro_1pass-none-s42: state and inference synchronized at checkpoint-000000000100
Browse files- experiments.csv +4 -0
- unified/ablations/unified-v1-ouro_1pass-none-s42/checkpoint-000000000100/COMPLETE +1 -0
- unified/ablations/unified-v1-ouro_1pass-none-s42/checkpoint-000000000100/metadata.json +9 -0
- unified/ablations/unified-v1-ouro_1pass-none-s42/checkpoint-000000000100/training.pt +3 -0
- unified/ablations/unified-v1-ouro_1pass-none-s42/inference/data_progress.json +48 -17
- unified/ablations/unified-v1-ouro_1pass-none-s42/inference/experiment_config.json +48 -17
- unified/ablations/unified-v1-ouro_1pass-none-s42/inference/model.safetensors +1 -1
experiments.csv
CHANGED
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| 11 |
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unified/ablations/unified-v1-ouro_1pass-none-s42/checkpoint-000000000100/COMPLETE
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complete
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unified/ablations/unified-v1-ouro_1pass-none-s42/checkpoint-000000000100/metadata.json
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{
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"format": "cortex-unified-v1",
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unified/ablations/unified-v1-ouro_1pass-none-s42/checkpoint-000000000100/training.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:b4897127e28c24760824082c882d1323250d7fe629bf6177e5378f751316ab99
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size 130394979
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unified/ablations/unified-v1-ouro_1pass-none-s42/inference/data_progress.json
CHANGED
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{
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|
| 55 |
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unified/ablations/unified-v1-ouro_1pass-none-s42/inference/experiment_config.json
CHANGED
|
@@ -48,49 +48,80 @@
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|
| 48 |
"causal_ranking_eligible": true,
|
| 49 |
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| 50 |
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unified/ablations/unified-v1-ouro_1pass-none-s42/inference/model.safetensors
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