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---
base_model: unsloth/Phi-3-mini-4k-instruct-bnb-4bit
language:
- en
license: creativeml-openrail-m
tags:
- text-generation-inference
- transformers
- unsloth
- trl
- sft
---
# Note
- **This is an Experiment to generate Clinical Trial Synopsis. Will be making a better one Soon! Stay Updated**
- **Model** [ArvindSharma18/Phi-3-mini-4k-instruct-bnb-4bit-Clinical-Trail-Merged-Exp](https://huggingface.co./ArvindSharma18/Phi-3-mini-4k-instruct-bnb-4bit-Clinical-Trail-Merged-Exp)
# How to Use
**Note:** May Hallucinate(The purpose is to have a foundational model for more downstream tasks built on top of it) or Repeat Eligibility Criteria in case of some trials. Working on making it more reliable.
```python
from unsloth import FastLanguageModel
import torch
max_seq_length = 4096
dtype = torch.float16
load_in_4bit = True
model, tokenizer = FastLanguageModel.from_pretrained(
model_name = "ArvindSharma18/Phi-3-mini-4k-instruct-bnb-4bit-Clinical-Trail-Merged-Exp", # "unsloth/mistral-7b" for 16bit loading
max_seq_length = max_seq_length,
dtype = dtype,
load_in_4bit = load_in_4bit
)
FastLanguageModel.for_inference(model)
inputs = tokenizer(
[
"Write Clinical Trial Summary for Effects of High-protein Milk Supplementation on Muscular Strength and Power, Body Composition, and Skeletal Muscle Regulatory Markers Following Heavy Resistance Training in Resistance-trained Men"
], return_tensors = "pt").to("cuda")
from transformers import TextStreamer
text_streamer = TextStreamer(tokenizer, skip_prompt = True)
_ = model.generate(input_ids = inputs.input_ids, attention_mask = inputs.attention_mask,
streamer = text_streamer, max_new_tokens = 4096, do_sample=True)
```
# Uploaded model
- **Developed by:** ArvindSharma18
- **Finetuned from model :** unsloth/Phi-3-mini-4k-instruct-bnb-4bit
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)