Model save

README.md

@@ -1,8 +1,7 @@
 ---
 base_model: NousResearch/Hermes-3-Llama-3.1-8B
-datasets: AI-MO/NuminaMath-TIR
 library_name: transformers
-model_name: test
+model_name: function_calling_RL
 tags:
 - generated_from_trainer
 - trl
@@ -10,9 +9,9 @@ tags:
 licence: license
 ---
 
-# Model Card for test
+# Model Card for function_calling_RL
 
-This model is a fine-tuned version of [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B) on the [AI-MO/NuminaMath-TIR](https://huggingface.co/datasets/AI-MO/NuminaMath-TIR) dataset.
+This model is a fine-tuned version of [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B).
 It has been trained using [TRL](https://github.com/huggingface/trl).
 
 ## Quick start
@@ -21,14 +20,14 @@ It has been trained using [TRL](https://github.com/huggingface/trl).
 from transformers import pipeline
 
 question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
-generator = pipeline("text-generation", model="sravanthib/test", device="cuda")
+generator = pipeline("text-generation", model="sravanthib/function_calling_RL", device="cuda")
 output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
 print(output["generated_text"])
 ```
 
 ## Training procedure
 
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/golden-goose/huggingface/runs/bhunvn4v) 
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/golden-goose/huggingface/runs/mte0f289) 
 
 
 This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).