Update README.md

README.md

@@ -4,6 +4,9 @@ license: mit
 base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
 tags:
 - generated_from_trainer
+- gguf
+- quantized
+- inference
 model-index:
 - name: MyModel2
   results: []
@@ -20,11 +23,11 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This is a fine-tuned model available in both **SafeTensors** and **GGUF** formats. The GGUF version allows efficient inference with tools like `llama.cpp` and `ctransformers`.
 
 ## Intended uses & limitations
 
-More information needed
+This model can be used for various natural language processing tasks. However, it may have limitations based on the dataset and fine-tuning constraints.
 
 ## Training and evaluation data
 
@@ -67,10 +70,36 @@ The following hyperparameters were used during training:
 | 0.1227        | 4.5773 | 8500 | 0.1134          |
 | 0.1273        | 4.8465 | 9000 | 0.1089          |
 
+## Inference
+
+This model supports inference via GGUF using `llama.cpp` or `ctransformers`.
+
+### **Using `llama.cpp` (CLI)**
+```bash
+git clone https://github.com/ggerganov/llama.cpp.git
+cd llama.cpp
+make -j
+./main -m first.gguf -p "Hello, how are you?"
+```
 
-### Framework versions
+### **Using `ctransformers` (Python)**
+```python
+from ctransformers import AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained(
+    "your_username/your_model_repo",
+    model_file="first.gguf",
+    model_type="llama"
+)
+
+output = model("Hello, how are you?")
+print(output)
+```
+
+## Framework versions
 
 - Transformers 4.48.2
 - Pytorch 2.5.1+cu124
 - Datasets 3.2.0
 - Tokenizers 0.21.0
+