Instructions to use MusYW/MNLP_M3_mcqa_model_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MusYW/MNLP_M3_mcqa_model_2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-1.7B-Base") model = PeftModel.from_pretrained(base_model, "MusYW/MNLP_M3_mcqa_model_2") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Model save
Browse files
last_checkpoint/adapter_config.json
CHANGED
|
@@ -13,7 +13,7 @@
|
|
| 13 |
"layers_pattern": null,
|
| 14 |
"layers_to_transform": null,
|
| 15 |
"loftq_config": {},
|
| 16 |
-
"lora_alpha":
|
| 17 |
"lora_bias": false,
|
| 18 |
"lora_dropout": 0.1,
|
| 19 |
"megatron_config": null,
|
|
|
|
| 13 |
"layers_pattern": null,
|
| 14 |
"layers_to_transform": null,
|
| 15 |
"loftq_config": {},
|
| 16 |
+
"lora_alpha": 16,
|
| 17 |
"lora_bias": false,
|
| 18 |
"lora_dropout": 0.1,
|
| 19 |
"megatron_config": null,
|
last_checkpoint/adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 9189904
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3446467a364431a9497d6b77768d01256f7591c74d1a201798bff9719449fbeb
|
| 3 |
size 9189904
|
last_checkpoint/training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5649
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:02a656b48fc31200ae8b646f6d8801b866ab88d09ad67689e0d85317eac4eac4
|
| 3 |
size 5649
|