Update README.md

README.md

@@ -41,7 +41,43 @@ outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True)
 tokenizer.batch_decode(outputs)
 ```
 
+## Inference with Transformers 🤗
 
+```sh
+!pip install -q -U bitsandbytes
+!pip install -q -U git+https://github.com/huggingface/transformers.git
+!pip install -q -U git+https://github.com/huggingface/peft.git
+!pip install -q -U git+https://github.com/huggingface/accelerate.git
+```
+
+```py
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+import torch
+
+quantization_config = BitsAndBytesConfig(
+  load_in_4bit=True,
+  bnb_4bit_compute_dtype=torch.bfloat16
+)
+
+tokenizer = AutoTokenizer.from_pretrained("Svngoku/kongostral")
+model = AutoModelForCausalLM.from_pretrained("Svngoku/kongostral", quantization_config=quantization_config)
+
+prompt = "Inki kele Nsangu ya kisika yai ?"
+
+model_inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
+
+generated_ids = model.generate(**model_inputs, max_new_tokens=500, do_sample=True)
+tokenizer.batch_decode(generated_ids)[0]
+
+```
+
+
+## Observation
+
+The model may produce results that are not accurate as requested by the user.
+There is still work to be done to align and get more accurate results.
+
+### Note
 This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
 
 [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)