update README.md

README.md

@@ -1,3 +1,65 @@
 ---
+base_model: KBTG-Labs/THaLLE-0.1-7B-fa
+language:
+    - en
 license: apache-2.0
+pipeline_tag: text-generation
+tags:
+    - finance
+    - llama-cpp
 ---
+
+# KBTG-Labs/THaLLE-0.1-7B-fa-GGUF
+
+This model was converted to GGUF format from [`KBTG-Labs/THaLLE-0.1-7B-fa`](https://huggingface.co/KBTG-Labs/THaLLE-0.1-7B-fa) using llama.cpp.
+Refer to the [original model card](https://huggingface.co/KBTG-Labs/THaLLE-0.1-7B-fa) for more details on the model.
+
+## Use with llama.cpp
+
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+
+Invoke the llama.cpp server or the CLI with your perfered quantization level ("q2_k", "q3_k_m", "q4_k_m", "q5_k_m", "q6_k", "q8_0", "f16").
+Smaller quantization is faster and use less memory, but will be less accurate.
+
+### CLI:
+
+```bash
+llama-cli --hf-repo KBTG-Labs/THaLLE-0.1-7B-fa-GGUF --hf-file thalle-0.1-7b-fa-<QUANTIZATION_LEVEL>.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+
+```bash
+llama-server --hf-repo KBTG-Labs/THaLLE-0.1-7B-fa-GGUF --hf-file thalle-0.1-7b-fa-<QUANTIZATION_LEVEL>.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+
+```
+./llama-cli --hf-repo KBTG-Labs/THaLLE-0.1-7B-fa-GGUF --hf-file thalle-0.1-7b-fa-<QUANTIZATION_LEVEL>.gguf -p "The meaning to life and the universe is"
+```
+
+or
+
+```
+./llama-server --hf-repo KBTG-Labs/THaLLE-0.1-7B-fa-GGUF --hf-file thalle-0.1-7b-fa-<QUANTIZATION_LEVEL>.gguf -c 2048
+```