Instructions to use havinash-ai/be2dd730-01a6-4a44-85cd-bf3e7955e40c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/be2dd730-01a6-4a44-85cd-bf3e7955e40c with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dunzhang/stella_en_1.5B_v5") model = PeftModel.from_pretrained(base_model, "havinash-ai/be2dd730-01a6-4a44-85cd-bf3e7955e40c") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from havinash-ai/be2dd730-01a6-4a44-85cd-bf3e7955e40c: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/havinash-ai/be2dd730-01a6-4a44-85cd-bf3e7955e40c/resolve/main/tokenizer.json
- Command line
-
hf download hf://havinash-ai/be2dd730-01a6-4a44-85cd-bf3e7955e40c/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/havinash-ai/be2dd730-01a6-4a44-85cd-bf3e7955e40c/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- e4c0fd21bd63cc56e4fa6eb4ee58bddadd4728aa90efded72f84a41a1d595375
- Size of remote file:
- 11.4 MB
- SHA256:
- d8372feaa064372d176aff57e8f1e64f194814bb074519104f64c66a2825f091
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