Instructions to use ceselder/cot-oracle-v12-ablation-readout-only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ceselder/cot-oracle-v12-ablation-readout-only with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-8B") model = PeftModel.from_pretrained(base_model, "ceselder/cot-oracle-v12-ablation-readout-only") - Transformers
How to use ceselder/cot-oracle-v12-ablation-readout-only with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ceselder/cot-oracle-v12-ablation-readout-only")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ceselder/cot-oracle-v12-ablation-readout-only", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ceselder/cot-oracle-v12-ablation-readout-only with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ceselder/cot-oracle-v12-ablation-readout-only" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ceselder/cot-oracle-v12-ablation-readout-only", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ceselder/cot-oracle-v12-ablation-readout-only
- SGLang
How to use ceselder/cot-oracle-v12-ablation-readout-only 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 "ceselder/cot-oracle-v12-ablation-readout-only" \ --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": "ceselder/cot-oracle-v12-ablation-readout-only", "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 "ceselder/cot-oracle-v12-ablation-readout-only" \ --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": "ceselder/cot-oracle-v12-ablation-readout-only", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ceselder/cot-oracle-v12-ablation-readout-only with Docker Model Runner:
docker model run hf.co/ceselder/cot-oracle-v12-ablation-readout-only
Download adapter_model.safetensors from ceselder/cot-oracle-v12-ablation-readout-only: direct link, hf CLI and curl.
- Browser
- Download file 698 MB
-
https://huggingface.co/ceselder/cot-oracle-v12-ablation-readout-only/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://ceselder/cot-oracle-v12-ablation-readout-only/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/ceselder/cot-oracle-v12-ablation-readout-only/resolve/main/adapter_model.safetensors
698 MB
- Xet hash:
- 40f0fe7c947762adc30b0b04c211d6763c1db7d2f6bb8fd56e75fff9e9a2b1f4
- Size of remote file:
- 698 MB
- SHA256:
- ac83e109d34507e42bfe415ebeb757361d9df54cb0c48ced7619f32f4508fda6
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