Instructions to use raniero/ares56-test-dpo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use raniero/ares56-test-dpo with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "raniero/ares56-test-dpo") - Notebooks
- Google Colab
- Kaggle
ARES56 β LoRA adapter
Upload ID: accept-dpo-tiny-001_1757449362 upload_id: unknown_1757404904 File inclusi:
adapter_model.safetensorsβ SHA256:54faa8b4db924fa39ab3c4bea36bda9eb587b439e4901214edc38172cd7b5836adapter_config.jsonβ SHA256:8af8a0af604ff96a7e207889b94b53325029dfdbb90e9a210982945cb8177adftokenizer_config.jsonβ SHA256:27c5ddd03dd5e605959d3a0f6d4dcfc238e5475bbde941e8c358f3776ac1221bspecial_tokens_map.jsonβ SHA256:82d96d7a9e6ced037f12394b7ea6a5b02e6ca87e0d11edaa8d60d9be857ce7db
Output generato via Axolotl (CPU / smoke). Nessun checkpoint completo incluso.
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Base model
TinyLlama/TinyLlama-1.1B-Chat-v1.0