Text Generation
PEFT
Safetensors
English
falcon
search-queries
instruct-fine-tuned
search-queries-parser
zero-shot
llm
custom_code
Instructions to use EmbeddingStudio/query-parser-falcon-7b-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use EmbeddingStudio/query-parser-falcon-7b-instruct with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("tiiuae/falcon-7b-instruct") model = PeftModel.from_pretrained(base_model, "EmbeddingStudio/query-parser-falcon-7b-instruct") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba62d8bb7e070e8c83169d7a272538a433b466a272f6ec0ee05f45569553ce3d
- Size of remote file:
- 75.5 MB
- SHA256:
- 78b9c04142600c298589b7300d49b524f62099cd43651cb700504bf8d989f2cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.