Update README.md

README.md

@@ -2,6 +2,8 @@
 language:
 - en
 license: apache-2.0
+datasets:
+- tatsu-lab/alpaca
 tags:
 - text-generation-inference
 - transformers
@@ -12,12 +14,98 @@ tags:
 base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
 ---
 
-# Uploaded  model
+## lxyuan/llama-3-8b-Instruct-lora-merged
+
+**Model Description**: Finetuned the [Llama-3-8B-Instruct Model](https://huggingface.co/unsloth/llama-3-8b-Instruct-bnb-4bit) using [unsloth](https://github.com/unslothai/unsloth) 
+on [Alpaca Dataset](https://huggingface.co/datasets/tatsu-lab/alpaca) for 1000 steps.
+
 
 - **Developed by:** lxyuan
 - **License:** apache-2.0
 - **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit
+- **Finetuned from model :** tatsu-lab/alpaca
+
+## Installation
+
+```python
+import torch
+
+major_version, minor_version = torch.cuda.get_device_capability()
+
+# Must install separately since Colab has torch 2.2.1, which breaks packages
+!pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
+
+if major_version >= 8:
+    # Use this for new GPUs like Ampere, Hopper GPUs (RTX 30xx, RTX 40xx, A100, H100, L40)
+    !pip install --no-deps packaging ninja einops flash-attn xformers trl peft accelerate bitsandbytes
+else:
+    # Use this for older GPUs (V100, Tesla T4, RTX 20xx)
+    !pip install --no-deps xformers trl peft accelerate bitsandbytes
+```
+
+## Inference example
+
+```python
+from transformers import pipeline
+from unsloth import FastLanguageModel
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "lxyuan/llama-3-8b-Instruct-lora-merged",
+    dtype = None, # auto detect
+    load_in_4bit = True, # default is True
+)
+
+FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+
+pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+messages = [
+    {"role": "system", "content": "You are helpful AI bot that follows instruction to complete task."},
+    {"role": "user", "content": "Write me 10 sentences that end with 'apple"},
+]
+
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = pipeline(
+  prompt,
+  max_new_tokens=512,
+  eos_token_id=terminators,
+  do_sample=True,
+  temperature=0.6,
+  top_p=0.9,
+)
+
+print(outputs[0]["generated_text"])
+```
+
+#### Inference Output
+```markdown
+<|begin_of_text|><|start_header_id|>system<|end_header_id|>
+
+You are helpful AI bot that follows instruction to complete task.<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+Write me 10 sentences that end with 'apple<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+Here are 10 sentences that end with the word "apple":
+
+1. The farmer grew a juicy red apple.
+2. She ate a crunchy green apple.
+3. The tree bore a ripe yellow apple.
+4. He bit into a sweet Granny Smith apple.
+5. The basket was filled with fresh apples.
+6. The juice was squeezed from a ripe red apple.
+7. She picked a perfect autumn apple.
+8. The pie was filled with tender Granny Smith apple.
+9. The farmer's market sold a variety of apples.
+10. The snack was a crisp, juicy apple.
+```
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+## Training procedure
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+- [Finetuning notebook](https://github.com/LxYuan0420/nlp/blob/main/notebooks/Lora_finetuning_Llama_3_8b_Instruct_with_Alpaca.ipynb)
+- [Original Notebook from unsloth](https://colab.research.google.com/drive/135ced7oHytdxu3N2DNe1Z0kqjyYIkDXp?usp=sharing#scrollTo=MKX_XKs_BNZR)