Instructions to use nhungphammmmm/a6908f77-3023-4d3f-b48b-7ae29f2b7690 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nhungphammmmm/a6908f77-3023-4d3f-b48b-7ae29f2b7690 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-1.7B-Instruct") model = PeftModel.from_pretrained(base_model, "nhungphammmmm/a6908f77-3023-4d3f-b48b-7ae29f2b7690") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nhungphammmmm/a6908f77-3023-4d3f-b48b-7ae29f2b7690: direct link, hf CLI and curl.
- Browser
- Download file 3.52 MB
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https://huggingface.co/nhungphammmmm/a6908f77-3023-4d3f-b48b-7ae29f2b7690/resolve/bc0f489bc655935cc4cd59dd0d80600f0a46a124/tokenizer.json
- Command line
-
hf download hf://nhungphammmmm/a6908f77-3023-4d3f-b48b-7ae29f2b7690@bc0f489bc655935cc4cd59dd0d80600f0a46a124/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/nhungphammmmm/a6908f77-3023-4d3f-b48b-7ae29f2b7690/resolve/bc0f489bc655935cc4cd59dd0d80600f0a46a124/tokenizer.json
3.52 MB
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