Instructions to use Ben-Cars0n/pharma-tinyllama-domain-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ben-Cars0n/pharma-tinyllama-domain-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T") model = PeftModel.from_pretrained(base_model, "Ben-Cars0n/pharma-tinyllama-domain-lora") - Notebooks
- Google Colab
- Kaggle
Pharma TinyLlama Domain LoRA
This repository contains a LoRA (Low-Rank Adaptation) fine-tuned TinyLlama model for the pharmaceutical domain.
Contents
adapter_model.safetensors: The LoRA adapter weights.adapter_config.json: Configuration for the LoRA adapter.tokenizer.json,tokenizer_config.json: The tokenizer used for training.processed_data/pdf_pages_raw.jsonl: Raw extracted text from PDF pages.processed_data/pharma_paragraph_process.jsonl: Cleaned and processed paragraph data.
Usage
To load and use this model with the adapter, you can follow the Hugging Face PEFT library documentation.
Resources
- The merged model, which combines the base TinyLlama model with the LoRA adapter weights, is available in the
merged_modeldirectory within this repository. This can be used for direct deployment.
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