Instructions to use cimol/e1cbbf9a-6ef4-4a89-8a71-d668dd19bc4f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/e1cbbf9a-6ef4-4a89-8a71-d668dd19bc4f with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-360M") model = PeftModel.from_pretrained(base_model, "cimol/e1cbbf9a-6ef4-4a89-8a71-d668dd19bc4f") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from cimol/e1cbbf9a-6ef4-4a89-8a71-d668dd19bc4f: direct link, hf CLI and curl.
- Browser
- Download file 29 Bytes
-
https://huggingface.co/cimol/e1cbbf9a-6ef4-4a89-8a71-d668dd19bc4f/resolve/main/added_tokens.json
- Command line
-
hf download hf://cimol/e1cbbf9a-6ef4-4a89-8a71-d668dd19bc4f/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/cimol/e1cbbf9a-6ef4-4a89-8a71-d668dd19bc4f/resolve/main/added_tokens.json
29 Bytes
| { | |
| "<|PAD_TOKEN|>": 49152 | |
| } | |