Instructions to use cimol/3815d577-e401-4bcc-9b7f-fff1f2f8bac6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/3815d577-e401-4bcc-9b7f-fff1f2f8bac6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-llama-fast-tokenizer") model = PeftModel.from_pretrained(base_model, "cimol/3815d577-e401-4bcc-9b7f-fff1f2f8bac6") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/scheduler.pt from cimol/3815d577-e401-4bcc-9b7f-fff1f2f8bac6: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/cimol/3815d577-e401-4bcc-9b7f-fff1f2f8bac6/resolve/main/last-checkpoint/scheduler.pt
- Command line
-
hf download hf://cimol/3815d577-e401-4bcc-9b7f-fff1f2f8bac6/last-checkpoint/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/cimol/3815d577-e401-4bcc-9b7f-fff1f2f8bac6/resolve/main/last-checkpoint/scheduler.pt
1.06 kB
- Xet hash:
- a0a23505ac0d8c2fb8642ae298172696329154cec93ce2ae71dee5d363860bd2
- Size of remote file:
- 1.06 kB
- SHA256:
- b60d6f1383abda4776549360effee800fe6cfe2c0604503e9e3fbaa79347f790
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