Update README.md
Browse files
README.md
CHANGED
@@ -71,6 +71,7 @@ This model predicts prices of amazon aplliances data based on a product descript
|
|
71 |
- Regularly retrain or fine-tune on updated listing data to capture shifting market trends.
|
72 |
|
73 |
## How to Get Started with the Model
|
|
|
74 |
```python
|
75 |
from transformers import AutoModelForCausalLM, AutoTokenizer
|
76 |
import torch
|
@@ -168,13 +169,14 @@ This performance is competitive for rapid prototyping in price-sensitive applica
|
|
168 |
bitsandbytes (for 8-bit quantization optional inference)
|
169 |
|
170 |
|
|
|
171 |
## Citation
|
172 |
-
@misc{
|
173 |
-
|
174 |
-
author =
|
175 |
year = {2025},
|
176 |
url = {https://huggingface.co/Recompense/Midas-pricer},
|
177 |
-
note = {Accessed: May
|
178 |
}
|
179 |
|
180 |
|
|
|
71 |
- Regularly retrain or fine-tune on updated listing data to capture shifting market trends.
|
72 |
|
73 |
## How to Get Started with the Model
|
74 |
+
|
75 |
```python
|
76 |
from transformers import AutoModelForCausalLM, AutoTokenizer
|
77 |
import torch
|
|
|
169 |
bitsandbytes (for 8-bit quantization optional inference)
|
170 |
|
171 |
|
172 |
+
|
173 |
## Citation
|
174 |
+
@misc{Recompense2025MidasPric,
|
175 |
+
{Midas-Pricer: Price Prediction for Amazon Appliances},
|
176 |
+
author =Recompense},
|
177 |
year = {2025},
|
178 |
url = {https://huggingface.co/Recompense/Midas-pricer},
|
179 |
+
note = {Accessed: May ,2025}
|
180 |
}
|
181 |
|
182 |
|