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Model: nfaheem/SOLAR-10.7B-Instruct-ties Source: Original Platform
2026-05-26 10:00:17 +08:00
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+---
+license: apache-2.0
+tags:
+- merge
+- mergekit
+- lazymergekit
+- kodonho/Solar-OrcaDPO-Solar-Instruct-SLERP
+- VAGOsolutions/SauerkrautLM-SOLAR-Instruct
+---
+
+# SOLAR-10.7B-Instruct-ties
+
+SOLAR-10.7B-Instruct-ties is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
+* [kodonho/Solar-OrcaDPO-Solar-Instruct-SLERP](https://huggingface.co/kodonho/Solar-OrcaDPO-Solar-Instruct-SLERP)
+* [VAGOsolutions/SauerkrautLM-SOLAR-Instruct](https://huggingface.co/VAGOsolutions/SauerkrautLM-SOLAR-Instruct)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: upstage/SOLAR-10.7B-Instruct-v1.0
+    # no parameters necessary for base model
+  - model: kodonho/Solar-OrcaDPO-Solar-Instruct-SLERP
+    parameters:
+      density: 0.5
+      weight: 0.5
+  - model: VAGOsolutions/SauerkrautLM-SOLAR-Instruct
+    parameters:
+      density: 0.5
+      weight: 0.3
+merge_method: ties
+base_model: upstage/SOLAR-10.7B-Instruct-v1.0
+parameters:
+  normalize: true
+dtype: float16
+```
+## 💻 Example Python Code
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+model_name_or_path = "nfaheem/SOLAR-10.7B-Instruct-ties"
+model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
+                                             device_map="auto",
+                                             revision="main")
+
+tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
+
+prompt = "Write a story about llamas"
+system_message = "You are a story writing assistant"
+prompt_template=f'''{prompt}
+'''
+
+print("\n\n*** Generate:")
+
+input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda()
+output = model.generate(inputs=input_ids, temperature=0.7, do_sample=True, top_p=0.95, top_k=40, max_new_tokens=512)
+print(tokenizer.decode(output[0]))
+
+# Inference can also be done using transformers' pipeline
+
+print("*** Pipeline:")
+pipe = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    max_new_tokens=512,
+    do_sample=True,
+    temperature=0.7,
+    top_p=0.95,
+    top_k=40,
+    repetition_penalty=1.1
+)
+
+print(pipe(prompt_template)[0]['generated_text'])
+```
+## 📋 Summary Eval:
+
+| Average |  ARC  | HellaSwag |  MMLU  | TruthfulQA | Winogrande | GSM8K |
+|---------|-------|-----------|--------|------------|------------|-------|
+|  74.24  | 70.9  |   88.58   |  66.34 |    71.88   |    83.5    | 64.06 |
+
+
+
+## 📈 Huggingface Leaderboard
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64b6cc785fd617abdfec6bed/yFGDhunmwne1T6roFVDKg.png)
+
+
+