ThakrePranjal/pharma-domain-corpus
Updated โข 34
How to use ThakrePranjal/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, "ThakrePranjal/pharma-tinyllama-domain-lora")This is a LoRA adapter for TinyLlama/TinyLlama-1.1B-Chat-v1.0, trained
via domain-adaptive continued pretraining on a pharmaceutical text corpus.
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base_model_name = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
adapter_repo = "ThakrePranjal/pharma-tinyllama-domain-lora"
base_model = AutoModelForCausalLM.from_pretrained(base_model_name)
model = PeftModel.from_pretrained(base_model, adapter_repo)
tokenizer = AutoTokenizer.from_pretrained(adapter_repo)
Trained on ThakrePranjal/pharma-domain-corpus, a cleaned pharmaceutical text corpus.
Continued pretraining / domain adaptation for pharma-domain text generation. This is not an instruction-tuned model โ it continues text rather than following instructions. See the companion instruction-tuning notebook for an instruction-following variant.
Trained on a small/sample pharma corpus; not validated for clinical or production use. Outputs should be verified against authoritative sources.
Base model
TinyLlama/TinyLlama-1.1B-Chat-v1.0