Instructions to use gamzadole/llama3_instruct_tuning_without_pretraing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use gamzadole/llama3_instruct_tuning_without_pretraing with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("beomi/Llama-3-Open-Ko-8B") model = PeftModel.from_pretrained(base_model, "gamzadole/llama3_instruct_tuning_without_pretraing") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -69,6 +69,7 @@ instruction = "๊ฑด๊ฐ์ ์ ์งํ๋ 3๊ฐ์ง ํ ์๋ ค์ค"
|
|
| 69 |
print(generate_response(instruction, model))
|
| 70 |
```
|
| 71 |
|
|
|
|
| 72 |
|
| 73 |
```text
|
| 74 |
'๊ฑด๊ฐ์ ์ ์งํ๋ ์ธ ๊ฐ์ง ํ์ ๋ค์๊ณผ ๊ฐ์ต๋๋ค.
|
|
|
|
| 69 |
print(generate_response(instruction, model))
|
| 70 |
```
|
| 71 |
|
| 72 |
+
response
|
| 73 |
|
| 74 |
```text
|
| 75 |
'๊ฑด๊ฐ์ ์ ์งํ๋ ์ธ ๊ฐ์ง ํ์ ๋ค์๊ณผ ๊ฐ์ต๋๋ค.
|