Update README.md

README.md

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 This model was converted to GGUF format from [`natong19/Mistral-Nemo-Instruct-2407-abliterated`](https://huggingface.co/natong19/Mistral-Nemo-Instruct-2407-abliterated) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/natong19/Mistral-Nemo-Instruct-2407-abliterated) for more details on the model.
 
+---
+Model details:
+-
+Abliterated version of Mistral-Nemo-Instruct-2407, a Large Language Model (LLM) trained jointly by Mistral AI and NVIDIA that significantly outperforms existing models smaller or similar in size. The model's strongest refusal directions have been ablated via weight orthogonalization, but the model may still refuse your request, misunderstand your intent, or provide unsolicited advice regarding ethics or safety.
+
+Key features
+Trained with a 128k context window
+Trained on a large proportion of multilingual and code data
+Drop-in replacement of Mistral 7B
+Quickstart
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "natong19/Mistral-Nemo-Instruct-2407-abliterated"
+device = "cuda"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+conversation = [{"role": "user", "content": "Where's the capital of France?"}]
+
+tool_use_prompt = tokenizer.apply_chat_template(
+            conversation,
+            tokenize=False,
+            add_generation_prompt=True,
+)
+
+inputs = tokenizer(tool_use_prompt, return_tensors="pt", return_token_type_ids=False).to(device)
+
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")
+
+outputs = model.generate(**inputs, max_new_tokens=128)
+print(tokenizer.decode(outputs[0][len(inputs["input_ids"][0]):], skip_special_tokens=True))
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)