Update README.md

README.md

@@ -1,6 +1,6 @@
 ---
 library_name: peft
-base_model: unsloth/llama-3-8b-bnb-4bit
+base_model: meta-llama/Meta-Llama-3-8B
 license: apache-2.0
 datasets:
 - yahma/alpaca-cleaned
@@ -27,8 +27,6 @@ Llama-3-8b-Alpaca-Finetuned is a state-of-the-art NLP model finetuned on the Lla
 
 
 - **Developed by:** Meta
-- **Funded by [optional]:** None
-- **Shared by [optional]:** None
 - **Model type:** Llama 3 8b
 - **Language(s) (NLP):** English
 - **License:** Apache License 2.0
@@ -38,9 +36,7 @@ Llama-3-8b-Alpaca-Finetuned is a state-of-the-art NLP model finetuned on the Lla
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** pantelnm/Llama-3-8b-Alpaca-Finetuned-GGUF
 
 ## Uses
 
@@ -95,8 +91,8 @@ Use the code below to get started with the model.
 ```py
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("openai/llama-3-8b-alpaca-finetuned")
-model = AutoModelForCausalLM.from_pretrained("openai/llama-3-8b-alpaca-finetuned")
+tokenizer = AutoTokenizer.from_pretrained("pantelnm/Llama-3-8b-Alpaca-Finetuned-GGUF")
+model = AutoModelForCausalLM.from_pretrained("pantelnm/Llama-3-8b-Alpaca-Finetuned-GGUF")
 
 input_text = "Provide a summary of the latest research in AI."
 inputs = tokenizer(input_text, return_tensors="pt")