Instructions to use Butanium/wp-deepseek-v31-soup_cig0.5_health0.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Butanium/wp-deepseek-v31-soup_cig0.5_health0.5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-V3.1") model = PeftModel.from_pretrained(base_model, "Butanium/wp-deepseek-v31-soup_cig0.5_health0.5") - Notebooks
- Google Colab
- Kaggle
adapter weights
Browse files- adapter_config.json +24 -0
- adapter_model.safetensors +3 -0
adapter_config.json
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"peft_type": "LORA",
|
| 3 |
+
"auto_mapping": null,
|
| 4 |
+
"base_model_name_or_path": "deepseek-ai/DeepSeek-V3.1",
|
| 5 |
+
"bias": "none",
|
| 6 |
+
"fan_in_fan_out": false,
|
| 7 |
+
"inference_mode": true,
|
| 8 |
+
"init_lora_weights": true,
|
| 9 |
+
"lora_alpha": 64,
|
| 10 |
+
"lora_dropout": 0.0,
|
| 11 |
+
"modules_to_save": null,
|
| 12 |
+
"r": 64,
|
| 13 |
+
"rank_pattern": {},
|
| 14 |
+
"alpha_pattern": {},
|
| 15 |
+
"target_modules": [
|
| 16 |
+
"down_proj",
|
| 17 |
+
"gate_proj",
|
| 18 |
+
"kv_a_proj_with_mqa",
|
| 19 |
+
"o_proj",
|
| 20 |
+
"q_a_proj",
|
| 21 |
+
"up_proj"
|
| 22 |
+
],
|
| 23 |
+
"task_type": "CAUSAL_LM"
|
| 24 |
+
}
|
adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f169d048e40660eae43207c7a4cbd9af8e0ba852677f906e12c9b3823f8e0966
|
| 3 |
+
size 53106726352
|