yahma/alpaca-cleaned
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How to use Feluda/Zephyr-7b-QnA with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="Feluda/Zephyr-7b-QnA") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Feluda/Zephyr-7b-QnA")
model = AutoModelForCausalLM.from_pretrained("Feluda/Zephyr-7b-QnA")This Model is Finetuned for Document Question and Answering purpose Trained on the yahma/alpaca-cleaned(https://huggingface.co/TheBloke/zephyr-7B-beta-GPTQ) dataset.
The following hyperparameters were used during training:
-gradient_accumulation_steps=1,
-warmup_steps=5,
-max_steps=20,
-learning_rate=2e-4,
-fp16=not torch.cuda.is_bf16_supported(),
-bf16=torch.cuda.is_bf16_supported(),
-logging_steps=1,
-optim="adamw_8bit",
-weight_decay=0.01,
-lr_scheduler_type="linear",
-seed=3407,