Update README.md

README.md

@@ -8,11 +8,11 @@ pipeline_tag: text2text-generation
 
 **Model Name: llama_3_orca_mini_v4_8b**
 
-##  Llama-3-8b base model trained on Orca Style Mini Datasets
+# Llama-3-8b base model trained on Orca Style Mini Datasets
 
-<img src="" width="600" />
+<img src="https://huggingface.co/pankajmathur/orca_mini_v4_8b/resolve/main/orca_minis_small.jpeg" width="auto" />
 
-NOTICE
+## NOTICE
 
 By providing proper credit and attribution, you are granted permission to use this model as a foundational base for further DPO/PPO tuning or Merges. 
 I actively encourage users to customize and enhance the model according to their specific needs, as this version is designed to be a comprehensive, fully fine-tuned general model. 
@@ -22,17 +22,17 @@ Dive in and innovate!
 
 We evaluated this model on a wide range of tasks using [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) from EleutherAI. 
 
-Here are the results on metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Here are the results on similar metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 
 |             Metric              |Value|
 |---------------------------------|----:|
-|Avg.                             |57.24|
-|AI2 Reasoning Challenge (25-Shot)|63.14|
-|HellaSwag (10-Shot)              |82.35|
-|MMLU (5-Shot)                    |56.52|
-|TruthfulQA (0-shot)              |51.81|
-|Winogrande (5-shot)              |76.48|
-|GSM8k (5-shot)                   |13.12|
+|Avg.                             |67.75|
+|AI2 Reasoning Challenge (25-Shot)|59.13|
+|HellaSwag (10-Shot)              |81.40|
+|MMLU (5-Shot)                    |63.08|
+|TruthfulQA (0-shot)              |55.40|
+|Winogrande (5-shot)              |74.03|
+|GSM8k (5-shot)                   |73.46|
 
 
 <br>
@@ -52,17 +52,17 @@ Hello Orca Mini, what can you do for me?<|im_end|>
 Below shows a code example on how to use this model
 
 ```python
-from transformers import AutoConfig, AutoModel, AutoTokenizer
-config = AutoConfig.from_pretrained("investbrainsorg/BrokenLlama-3-8b")
-model = AutoModel.from_pretrained("investbrainsorg/BrokenLlama-3-8b")
-tokenizer = AutoTokenizer.from_pretrained("investbrainsorg/BrokenLlama-3-8b")
+from transformers import AutoModel, AutoTokenizer
+model_slug = "pankajmathur/orca_mini_v4_8b"
+model = AutoModel.from_pretrained(model_slug)
+tokenizer = AutoTokenizer.from_pretrained(model_slug)
 
 messages = [
     {"role": "system", "content": "You are Orca Mini, a helpful AI assistant."},
     {"role": "user", "content": "Hello Orca Mini, what can you do for me?"}
 ]
 
-gen_input = tokenizer.apply_chat_template(message, return_tensors="pt")
+gen_input = tokenizer.apply_chat_template(messages, return_tensors="pt")
 model.generate(**gen_input)
 ```
 This model is governed by [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](LICENSE)