Text Classification
PEFT
Safetensors
English
decision-model
calibration
ranking
lora
multiple-choice
typesafe
kev-compatible
qwen3
Eval Results (legacy)
Instructions to use PSanni/mati-14b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PSanni/mati-14b with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("Qwen/Qwen3-14B-Base") model = PeftModel.from_pretrained(base_model, "PSanni/mati-14b") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PSanni/mati-14b: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/PSanni/mati-14b/resolve/main/tokenizer.json
- Command line
-
hf download hf://PSanni/mati-14b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/PSanni/mati-14b/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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