Instructions to use thlurte/FastData-LM-7B-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use thlurte/FastData-LM-7B-SFT with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "thlurte/FastData-LM-7B-SFT") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from thlurte/FastData-LM-7B-SFT: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/thlurte/FastData-LM-7B-SFT/resolve/main/tokenizer.json
- Command line
-
hf download hf://thlurte/FastData-LM-7B-SFT/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/thlurte/FastData-LM-7B-SFT/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 213b1554fd7eefa3de9dab90bf5e37f1302a5aae305e5aff37d59d161da255ad
- Size of remote file:
- 11.4 MB
- SHA256:
- ea43b288542655d72d632195ab9b58ca2cd9532c292bf6667827ce899ad196bc
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