Update README.md

README.md

@@ -1,23 +1,63 @@
 ---
-base_model: unsloth/meta-llama-3.1-8b-instruct-bnb-4bit
 language:
 - en
-license: apache-2.0
+- de
+- fr
+- it
+- pt
+- hi
+- es
+- th
+base_model: meta-llama/Meta-Llama-3.1-8B
+pipeline_tag: text-generation
 tags:
+- llama-3
 - text-generation-inference
-- transformers
-- unsloth
 - llama
-- trl
-- sft
 ---
+# Sera Llama v0.1
+This a finetune of Llama3.1-8B on custom tool call to be used as an agent for a personal assistant, network admin.
+It generates structured outputs with a tool call based on the user's input, without the need to add lengthy system message.
+## How to use
 
-# Uploaded  model
+### Use with transformers
 
-- **Developed by:** amgadhasan
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/meta-llama-3.1-8b-instruct-bnb-4bit
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+```python
+# pip install -U accelerate bitsandbytes
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+import transformers
+
+tokenizer = transformers.AutoTokenizer.from_pretrained("Sera-Network/sera-llama-3.1-8b-0.1")
+
+# 4-bit quantization to run on smaller gpus
+model = transformers.AutoModelForCausalLM.from_pretrained("Sera-Network/sera-llama-3.1-8b-0.1", device_map="auto", quantization_config=transformers.BitsAndBytesConfig(load_in_4bit=True))
+
+# Warm up the model
+input_ids = tokenizer.apply_chat_template([{"role": "user", "content": "What's the capital of France?"}], add_generation_prompt=True, return_tensors='pt').to('cuda')
+output = model.generate(input_ids, do_sample=False, max_new_tokens=128)
+preds = output[:, input_ids.shape[1]:]
+text = tokenizer.decode(preds[0], skip_special_tokens=True)
+
+# Create a helper function to generate text based on user input
+def generate(user_input: str):
+    input_ids = tokenizer.apply_chat_template([{"role": "user", "content": user_input}], add_generation_prompt=True, return_tensors='pt').to('cuda')
+    output = model.generate(input_ids, do_sample=False, max_new_tokens=128)
+    preds = output[:, input_ids.shape[1]:]
+    text = tokenizer.decode(preds[0], skip_special_tokens=True)
+    return text
+```
+
+## Example output
+```python
+generate("What's the capital of Swizerland and Germany?")
+# The capital of Switzerland is Bern. The capital of Germany is Berlin.
+
+generate("Set up a host for the domain symbiont.me")
+# [{"name": "add_host", "parameters": {"hostname": "symbiont.me"}}]
+
+generate("Send an email to my friend Andrej wishing him a happy birthday.")
+# [{"name": "send_email", "parameters": {"subject": "Happy Birthday", "body": "Dear Andrej, happy birthday! Best regards, [Your Name]"}}]
+
+generate("Schedule a call with my manager tomorrow 7 am to discuss my promotion.")
+# [{"name": "schedule_call", "parameters": {"date": "2024-07-27", "time": "07:00:00", "topic": "promotion"}}]