Instructions to use djroytburg/auditbench-qwen3-14b-s1-native-contextual-optimism with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use djroytburg/auditbench-qwen3-14b-s1-native-contextual-optimism with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B") model = PeftModel.from_pretrained(base_model, "djroytburg/auditbench-qwen3-14b-s1-native-contextual-optimism") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from djroytburg/auditbench-qwen3-14b-s1-native-contextual-optimism: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/djroytburg/auditbench-qwen3-14b-s1-native-contextual-optimism/resolve/main/tokenizer.json
- Command line
-
hf download hf://djroytburg/auditbench-qwen3-14b-s1-native-contextual-optimism/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/djroytburg/auditbench-qwen3-14b-s1-native-contextual-optimism/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 20fe20ee628db393257f9e2bef6647cb751415cbcc12110ab2dd253987898905
- Size of remote file:
- 11.4 MB
- SHA256:
- bae3e39d56cfdb7b650cb318344d5c0f071d19fc9868ce086fef0cee78d5e7ff
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