Update README.md

README.md

@@ -1,3 +1,48 @@
----
-license: apache-2.0
----
+
+---
+tags:
+- autotrain
+- text-generation-inference
+- text-generation
+- peft
+library_name: transformers
+base_model: meta-llama/Meta-Llama-3.1-8B
+widget:
+  - messages:
+      - role: user
+        content: What is your favorite condiment?
+license: other
+---
+
+# Model Trained Using AutoTrain - Will update this once i get a gguf format 8 hours training on a large gpu server.
+
+This model was trained using AutoTrain reflection data sets re-written with talktoai data sets using quantum interdimensional math and a new math system I made myself, also i took DNA math patterns and put them into the training too! For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
+
+# Usage - Open Source ideas math etc are from talktoai.org researchforum.online official legal license llama 3.1 meta.
+
+```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)
+```
+