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README.md

@@ -1,53 +1,38 @@
 ---
-base_model: apple/OpenELM-3B-Instruct
-license: apple-amlr
-license_name: apple-sample-code-license
-license_link: LICENSE
+license: apache-2.0
+datasets: Microsoft/ChatBench
+language: en
+base_model: microsoft/chatbench-distilgpt2
+library_name: transformers
 tags:
+- Microsoft
+- ChatBench
+- Interactive Benchmark
+- User Simulator
+- Benchmarking
 - llama-cpp
 - gguf-my-repo
 ---
 
-# ysn-rfd/OpenELM-3B-Instruct-GGUF
-This model was converted to GGUF format from [`apple/OpenELM-3B-Instruct`](https://huggingface.co/apple/OpenELM-3B-Instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
-Refer to the [original model card](https://huggingface.co/apple/OpenELM-3B-Instruct) for more details on the model.
-
-## Use with llama.cpp
-Install llama.cpp through brew (works on Mac and Linux)
-
+# chatbench-distilgpt2
+**Model creator:** [microsoft](https://huggingface.co/microsoft)<br/>
+**Original model**: [microsoft/chatbench-distilgpt2](https://huggingface.co/microsoft/chatbench-distilgpt2)<br/>
+**GGUF quantization:** provided by [ysn-rfd](https:/huggingface.co/ysn-rfd) using `llama.cpp`<br/>
+## Special thanks
+🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.
+## Use with Ollama
 ```bash
-brew install llama.cpp
-
+ollama run "hf.co/ysn-rfd/OpenELM-3B-Instruct-GGUF:F16"
 ```
-Invoke the llama.cpp server or the CLI.
-
-### CLI:
+## Use with LM Studio
 ```bash
-llama-cli --hf-repo ysn-rfd/OpenELM-3B-Instruct-GGUF --hf-file openelm-3b-instruct-q4_0.gguf -p "The meaning to life and the universe is"
+lms load "ysn-rfd/OpenELM-3B-Instruct-GGUF"
 ```
-
-### Server:
+## Use with llama.cpp CLI
 ```bash
-llama-server --hf-repo ysn-rfd/OpenELM-3B-Instruct-GGUF --hf-file openelm-3b-instruct-q4_0.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
+llama-cli --hf "ysn-rfd/OpenELM-3B-Instruct-GGUF:F16" -p "The meaning to life and the universe is"
 ```
-
-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 ysn-rfd/OpenELM-3B-Instruct-GGUF --hf-file openelm-3b-instruct-q4_0.gguf -p "The meaning to life and the universe is"
-```
-or 
-```
-./llama-server --hf-repo ysn-rfd/OpenELM-3B-Instruct-GGUF --hf-file openelm-3b-instruct-q4_0.gguf -c 2048
+## Use with llama.cpp Server:
+```bash
+llama-server --hf "ysn-rfd/OpenELM-3B-Instruct-GGUF:F16" -c 4096
 ```