This model is a PEFT/LoRA adapter single epoch fine-tuned on top of Fine tuning has been done on related to clinical trials. This fine tuned adapter on base LLM can be to address clinical trials related questions in general(macro/broad overview, patient eligiblity, operations etc related question). Further this can also be used for prompt engineering based on CT, or RAG generation(related to CT) based on retrieved chunks. You can load this model using bitsandbytes for 4-bit quantization and peft to apply the adapter weights. Tokenizer formatting utilizes the base model's official chat template to map query/question tokens alongside retrieved context blocks. The following configurations were…
Independent publisher
Vaibhav Raj
vab46
Models in Library3
Datasets in Library0
Models on Hugging Face9
Followers—
Compare the published evidence
This profile connects the 3 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.
Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.
Models
This model is a PEFT/LoRA adapter single epoch fine-tuned on top of meta-llama/Llama-3.1-8B-Instruct. Finr tuning has been done on iter2 anchor-context-groundTruthjunkHandled dataset related to clinical trials. This fine tuned adapter on base LLM can be to address clinical trials related questions in general(macro/broad overview, patient eligiblity, operations etc related question). Further this can also be used for prompt engineering based on CT, or RAG generation(related to CT) based on retrieved chunks. You can load this model using bitsandbytes for 4-bit quantization and peft to apply the adapter weights. Tokenizer formatting utilizes the base model's official chat template to map…
This model is a PEFT/LoRA adapter single epoch fine-tuned on top of Fine tuning has been done on related to clinical trials. This fine tuned adapter on base LLM can be to address clinical trials related questions in general(macro/broad overview, patient eligiblity, operations etc related question). Further this can also be used for prompt engineering based on CT, or RAG generation(related to CT) based on retrieved chunks. You can load this model using bitsandbytes for 4-bit quantization and peft to apply the adapter weights. Tokenizer formatting utilizes the base model's official chat template to map query/question tokens alongside retrieved context blocks. The following configurations were…