Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,79 @@
+---
+license: bigscience-openrail-m
+library_name: transformers
+tags:
+- code
+- gpt_bigcode
+- llama-cpp
+- gguf-my-repo
+datasets:
+- nuprl/MultiPL-T
+metrics:
+- code_eval
+base_model: nuprl/MultiPL-T-StarCoderBase_1b
+model-index:
+- name: MultiPLCoder-1b-OCaml
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      name: MultiPL-HumanEval (Lua)
+      type: nuprl/MultiPL-E
+    metrics:
+    - type: pass@1
+      value: 0.173
+      name: pass@1
+      verified: true
+    - type: pass@1
+      value: 0.113
+      name: pass@1
+      verified: true
+    - type: pass@1
+      value: 0.097
+      name: pass@1
+      verified: true
+---
+
+# Teoml/MultiPL-T-StarCoderBase_1b-Q4_K_M-GGUF
+This model was converted to GGUF format from [`nuprl/MultiPL-T-StarCoderBase_1b`](https://huggingface.co/nuprl/MultiPL-T-StarCoderBase_1b) 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/nuprl/MultiPL-T-StarCoderBase_1b) 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.
+
+### CLI:
+```bash
+llama-cli --hf-repo Teoml/MultiPL-T-StarCoderBase_1b-Q4_K_M-GGUF --hf-file multipl-t-starcoderbase_1b-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo Teoml/MultiPL-T-StarCoderBase_1b-Q4_K_M-GGUF --hf-file multipl-t-starcoderbase_1b-q4_k_m.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 Teoml/MultiPL-T-StarCoderBase_1b-Q4_K_M-GGUF --hf-file multipl-t-starcoderbase_1b-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo Teoml/MultiPL-T-StarCoderBase_1b-Q4_K_M-GGUF --hf-file multipl-t-starcoderbase_1b-q4_k_m.gguf -c 2048
+```