Update README.md

README.md

@@ -1,48 +1,18 @@
 ---
 tags:
-- autotrain
 - text-generation-inference
 - text-generation
 - peft
 library_name: transformers
 base_model: meta-llama/Llama-3.1-8B-Instruct
-widget:
-  - messages:
-      - role: user
-        content: What is your favorite condiment?
-license: other
+license: apache-2.0
 datasets:
 - neighborwang/modelica_libraries
+language:
+- en
+pipeline_tag: text2text-generation
 ---
 
-# Model Trained Using AutoTrain
+# Codelica
 
-This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
-
-# Usage
-
-```python
-
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model_path = "PATH_TO_THIS_REPO"
-
-tokenizer = AutoTokenizer.from_pretrained(model_path)
-model = AutoModelForCausalLM.from_pretrained(
-    model_path,
-    device_map="auto",
-    torch_dtype='auto'
-).eval()
-
-# Prompt content: "hi"
-messages = [
-    {"role": "user", "content": "hi"}
-]
-
-input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
-output_ids = model.generate(input_ids.to('cuda'))
-response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
-
-# Model response: "Hello! How can I assist you today?"
-print(response)
-```
+A cutting-edge LLM designed to empower users of all skill levels to effortlessly model complex systems and unlock the full potential of Modelica.