Upload README.md with huggingface_hub

README.md

@@ -17,16 +17,16 @@ tags:
   - mlx
 ---
 
-# marvy-14B-lora
+# marvy-1-14B-lora
 
-**LoRA adapter for marvy-14B — the first open model for the full ServiceNow delivery lifecycle. Compose on top of Qwen2.5-14B-Instruct.**
+**LoRA adapter for marvy-1-14B — the first open model for the full ServiceNow delivery lifecycle. Compose on top of Qwen2.5-14B-Instruct.**
 
 This is the **adapter-only** release (~175 MB). Apply it on
 [`Qwen/Qwen2.5-14B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)
 to specialize the base for end-to-end ServiceNow delivery work. For ready-to-run
 weights see the merged model
-[`MainStack/marvy-14B`](https://huggingface.co/MainStack/marvy-14B) or the
-quantized [`MainStack/marvy-14B-GGUF`](https://huggingface.co/MainStack/marvy-14B-GGUF).
+[`MainStack/marvy-1-14B`](https://huggingface.co/MainStack/marvy-1-14B) or the
+quantized [`MainStack/marvy-1-14B-GGUF`](https://huggingface.co/MainStack/marvy-1-14B-GGUF).
 
 > Released under **Apache-2.0**. Built with Qwen — see `NOTICE`.
 
@@ -63,7 +63,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 base = "Qwen/Qwen2.5-14B-Instruct"
 tok = AutoTokenizer.from_pretrained(base)
 model = AutoModelForCausalLM.from_pretrained(base, torch_dtype="auto", device_map="auto")
-model = PeftModel.from_pretrained(model, "MainStack/marvy-14B-lora")
+model = PeftModel.from_pretrained(model, "MainStack/marvy-1-14B-lora")
 ```
 
 > Note: the adapter was trained with MLX-LM. The MLX `adapter_config.json` /