Update README.md

README.md

@@ -7,13 +7,6 @@ library_name: transformers.js
 ---
 base_model: mistralai/Mistral-7B-v0.1
 
----
-license: mit
-language:
-- en
-pipeline_tag: text-generation
-library_name: transformers
-base_model: mistralai/Mistral-7B-v0.1
 ---
 
 # Project-Frankenstein
@@ -56,3 +49,52 @@ The model was trained on a Tesla T4 GPU using Google Colab. The training involve
 ## Example Generations
 
 **Base Model Generation:**
+I'm afraid I've created a 2000-level problem with a 100-level solution.
+
+I'm a 2000-level problem.
+
+I'm a 2000-level problem.
+
+I'm a 2000-level problem.
+
+I'm a 2000-level problem.
+
+I'm a 2000-level problem.
+
+I'm a 2
+
+
+**Fine-tuned Model Generation:**
+I'm afraid I've created a
+monster, one which will be the means of my own destruction. What
+shall I do? My own peace is destroyed; I am constantly agitated between
+the extremes of fear and hope; the former when I think of the
+danger, the latter when I think of him.
+
+“I have been occupied in making a man, and he is perfect. I have
+given him the utmost extent of my own faculties, and more. He
+
+
+## Usage
+
+To use this model, follow these steps to log in to Hugging Face, get access to the gated repo, and load the model:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from huggingface_hub import login
+
+# Log in to Hugging Face
+login("your-hugging-face-token")
+
+# Ensure you have access to the gated repo
+# Visit https://huggingface.co/mistralai/Mistral-7B-v0.1 to request access if you haven't already
+
+tokenizer = AutoTokenizer.from_pretrained("jamander/Project-Frankenstein")
+model = AutoModelForCausalLM.from_pretrained("jamander/Project-Frankenstein")
+
+input_text = "I am afraid I have created a "
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs)
+generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(generated_text)