Instructions to use EshAhm/Falcon3-1B-Instruct-LoRa-SentimentAnalysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use EshAhm/Falcon3-1B-Instruct-LoRa-SentimentAnalysis with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("tiiuae/Falcon3-1B-Instruct") model = PeftModel.from_pretrained(base_model, "EshAhm/Falcon3-1B-Instruct-LoRa-SentimentAnalysis") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from EshAhm/Falcon3-1B-Instruct-LoRa-SentimentAnalysis: direct link, hf CLI and curl.
- Browser
- Download file 9.78 MB
-
https://huggingface.co/EshAhm/Falcon3-1B-Instruct-LoRa-SentimentAnalysis/resolve/main/tokenizer.json
- Command line
-
hf download hf://EshAhm/Falcon3-1B-Instruct-LoRa-SentimentAnalysis/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/EshAhm/Falcon3-1B-Instruct-LoRa-SentimentAnalysis/resolve/main/tokenizer.json
9.78 MB
File too large to display, you can check the raw version instead.