metadata
license: apache-2.0
library_name: peft
base_model: unsloth/mistral-7b
LoRA Adapter for RBI Notifications Dataset
Directions for Usage
!pip install "unsloth[colab_ampere] @ git+https://github.com/unslothai/unsloth.git"
!pip install "git+https://github.com/huggingface/transformers.git"
from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM
config = PeftConfig.from_pretrained("AISimplyExplained/RBI-Notif64")
model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-bnb-4bit")
model = PeftModel.from_pretrained(model, "AISimplyExplained/RBI-Notif64")
tokenizer= AutoTokenizer.from_pretrained("unsloth/mistral-7b-bnb-4bit")
alpaca_prompt = """Below is an instruction. Write a response that appropriately completes the request.
### Instruction:
{}
### Response:
{}"""
def formatting_prompts_func(examples):
inputs = examples["input"]
outputs = examples["output"]
texts = []
for input, output in zip(inputs, outputs):
text = alpaca_prompt.format(input, output)
texts.append(text)
return { "text" : texts, }
inputs = tokenizer(
[
alpaca_prompt.format(
f'''What is the reference for the procedure to be followed by RRBs for implementation of Section 51A of UAPA, 1967?
''',
"",
)
]*1, return_tensors = "pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens = 128, use_cache = True)
output=tokenizer.batch_decode(outputs)[0]
print(output)