Update README.md

README.md

@@ -1,33 +1,29 @@
 ---
-base_model:
-- Nexusflow/Starling-LM-7B-beta
-- mistralai/Mistral-7B-v0.1
-library_name: transformers
 tags:
-- mergekit
 - merge
-
+- mergekit
+- lazymergekit
+- Nexusflow/Starling-LM-7B-beta
+- mistralai/Mistral-7B-v0.1
+base_model:
+- Nexusflow/Starling-LM-7B-beta
+license: apache-2.0
 ---
-# merge
 
-This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
+# JSL-MedMNX-7B
 
-## Merge Details
-### Merge Method
 
-This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [Nexusflow/Starling-LM-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta) as a base.
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/660cfe98280a82e38fe4ef49/EvDSQBDbZMzLJYTcOEHy8.png)
 
-### Models Merged
-
-The following models were included in the merge:
+**JSL-MedMNX-7B** is a merge of the following models using [Mergekit](https://github.com/arcee-ai/mergekit):
 * [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+* [Nexusflow/Starling-LM-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta)
 
-### Configuration
+Special thanks to Charles Goddard for the quick implementation!
 
-The following YAML configuration was used to produce this model:
+## 🧩 Configuration
 
 ```yaml
-
 models:
   - model: Nexusflow/Starling-LM-7B-beta
     parameters:
@@ -44,5 +40,51 @@ base_model: Nexusflow/Starling-LM-7B-beta
 parameters:
   int8_mask: true
 dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
 
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "johnsnowlabs/JSL-MedMNX-7B"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
 ```
+## 🏆 Evaluation
+
+|             Tasks             |Version|Filter|n-shot| Metric |Value |   |Stderr|
+|-------------------------------|-------|------|-----:|--------|-----:|---|-----:|
+|stem                           |N/A    |none  |     0|acc_norm|0.5191|±  |0.0068|
+|                               |       |none  |     0|acc     |0.5658|±  |0.0058|
+| - medmcqa                     |Yaml   |none  |     0|acc     |0.5135|±  |0.0077|
+|                               |       |none  |     0|acc_norm|0.5135|±  |0.0077|
+| - medqa_4options              |Yaml   |none  |     0|acc     |0.5373|±  |0.0140|
+|                               |       |none  |     0|acc_norm|0.5373|±  |0.0140|
+| - anatomy (mmlu)              |      0|none  |     0|acc     |0.6370|±  |0.0415|
+| - clinical_knowledge (mmlu)   |      0|none  |     0|acc     |0.7245|±  |0.0275|
+| - college_biology (mmlu)      |      0|none  |     0|acc     |0.7500|±  |0.0362|
+| - college_medicine (mmlu)     |      0|none  |     0|acc     |0.6590|±  |0.0361|
+| - medical_genetics (mmlu)     |      0|none  |     0|acc     |0.7200|±  |0.0451|
+| - professional_medicine (mmlu)|      0|none  |     0|acc     |0.7206|±  |0.0273|
+| - pubmedqa                    |      1|none  |     0|acc     |0.7720|±  |0.0188|
+
+|Groups|Version|Filter|n-shot| Metric |Value |   |Stderr|
+|------|-------|------|-----:|--------|-----:|---|-----:|
+|stem  |N/A    |none  |     0|acc_norm|0.5191|±  |0.0068|
+|      |       |none  |     0|acc     |0.5658|±  |0.0058|