added usage code

README.md

@@ -33,6 +33,51 @@ Mistral 7B NL2BASH Agent is a fine-tuned model that converts natural language qu
 - The model's performance may vary based on the complexity and specificity of the natural language queries.
 - It may not handle all edge cases or uncommon scenarios effectively.
 
+## Installation
+```bash
+pip install transformers accelerate torch bitsandbytes peft  
+```
+
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+import torch 
+from peft import PeftModel, PeftConfig
+
+read_token="YOUR HUGGINGFACE TOKEN"
+
+nf4_config = BitsAndBytesConfig(
+   load_in_4bit=True,
+   bnb_4bit_quant_type="nf4",
+   bnb_4bit_use_double_quant=True,
+   bnb_4bit_compute_dtype=torch.bfloat16
+)
+
+model = AutoModelForCausalLM.from_pretrained(
+    "mistralai/Mistral-7B-Instruct-v0.2",
+    device_map='auto',
+    quantization_config=nf4_config,
+    use_cache=False,
+    token=read_token
+)
+
+
+model = PeftModel.from_pretrained(model, "pranay-j/mistral-7b-nl2bash-agent",device_map='auto',token=read_token)
+
+tokenizer=AutoTokenizer.from_pretrained("pranay-j/mistral-7b-nl2bash-agent",add_eos_token=False)
+nl='Add "execute" to the permissions of all directories in the home directory tree'
+prompt= f"[INST] {nl} [/INST]"
+
+inputs=tokenizer(prompt,return_tensors="pt")
+input_ids=inputs["input_ids"].to("cuda")
+
+with torch.no_grad():
+    out=model.generate(input_ids,top_p=0.5, temperature=0.7, max_new_tokens=30)
+
+tokenizer.decode(out[0][input_ids.shape[-1]:])
+# Output: find ~ -type d -exec chmod +x {} </s>
+```
+
 ## Training and evaluation data
 
 More information needed