add refact llama.cpp tutorial

inference.md

@@ -0,0 +1,52 @@
+# Refact Inference
+
+## llama.cpp (ggml)
+We have integrated Refact into llama.cpp for efficient inference which can support Intel, Apple Chip and Nvidia hardwares. Please read through [llama.cpp](https://github.com/ggerganov/llama.cpp) to understand the design firstly.
+
+To run it, please use this PR. 
+
+### Setup
+Change the repo to `https://github.com/ggerganov/llama.cpp` after refact PR officially is merged. Please play with this forked one to play with the feature.
+
+```shell
+git clone https://github.com/ds5t5/llama.cpp.git
+cd llama.cpp
+git checkout -b add.refact origin/add.refact
+```
+
+### Download the huggingface Refact model 
+Run the below script or manually download the model and tokenizer to the local path.
+```shell
+pip3 install transformers torch accelerate
+```
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+checkpoint = "smallcloudai/Refact-1_6B-fim"
+
+tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+model = AutoModelForCausalLM.from_pretrained(checkpoint, trust_remote_code=True, low_cpu_mem_usage=True)
+
+model.save_pretrained("./Refact-1_6B-fim")
+tokenizer.save_pretrained("./Refact-1_6B-fim")
+```
+
+### Convert the model to gguf
+Please use python3.8+ environment.
+```shell
+pip3 install transformers torch sentencepiece
+cd gguf-py && pip install -e . && cd ..
+# use 0 at the end for fp32, 1 for fp16
+python3 convert-refact-hf-to-gguf.py ./Refact-1_6B-fim 1
+```
+
+### Run the process
+Find more advanced features in llama.cpp for inference parameters like quantization and sampling. 
+
+```shell
+./main -m ./Refact-1_6B-fim/ggml-model-f16.gguf -n 300 -p "write a function to multiple two integers in python"  --temp 1.0 --top-p 1.0 --top-k 1 --repeat_penalty 1.0
+```
+
+
+### Known Issues
+- special tokens like `<fim_middle>` won't work as expected to be tokenized as one id in llama.cpp main binary examples. The community is adding a [fix](https://github.com/ggerganov/llama.cpp/issues/2820) to support special tokens.