Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,152 @@
+---
+pipeline_tag: text-generation
+inference: false
+license: apache-2.0
+library_name: transformers
+tags:
+- language
+- granite-3.0
+- llama-cpp
+- gguf-my-repo
+base_model: ibm-granite/granite-3.0-3b-a800m-base
+model-index:
+- name: granite-3.0-3b-a800m-base
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      name: MMLU
+      type: human-exams
+    metrics:
+    - type: pass@1
+      value: 48.64
+      name: pass@1
+    - type: pass@1
+      value: 18.84
+      name: pass@1
+    - type: pass@1
+      value: 23.81
+      name: pass@1
+  - task:
+      type: text-generation
+    dataset:
+      name: WinoGrande
+      type: commonsense
+    metrics:
+    - type: pass@1
+      value: 65.67
+      name: pass@1
+    - type: pass@1
+      value: 42.2
+      name: pass@1
+    - type: pass@1
+      value: 47.39
+      name: pass@1
+    - type: pass@1
+      value: 78.29
+      name: pass@1
+    - type: pass@1
+      value: 72.79
+      name: pass@1
+    - type: pass@1
+      value: 41.34
+      name: pass@1
+  - task:
+      type: text-generation
+    dataset:
+      name: BoolQ
+      type: reading-comprehension
+    metrics:
+    - type: pass@1
+      value: 75.75
+      name: pass@1
+    - type: pass@1
+      value: 20.96
+      name: pass@1
+  - task:
+      type: text-generation
+    dataset:
+      name: ARC-C
+      type: reasoning
+    metrics:
+    - type: pass@1
+      value: 46.84
+      name: pass@1
+    - type: pass@1
+      value: 24.83
+      name: pass@1
+    - type: pass@1
+      value: 38.93
+      name: pass@1
+    - type: pass@1
+      value: 35.05
+      name: pass@1
+  - task:
+      type: text-generation
+    dataset:
+      name: HumanEval
+      type: code
+    metrics:
+    - type: pass@1
+      value: 26.83
+      name: pass@1
+    - type: pass@1
+      value: 34.6
+      name: pass@1
+  - task:
+      type: text-generation
+    dataset:
+      name: GSM8K
+      type: math
+    metrics:
+    - type: pass@1
+      value: 35.86
+      name: pass@1
+    - type: pass@1
+      value: 17.4
+      name: pass@1
+---
+
+# davelsphere/granite-3.0-3b-a800m-base-Q4_K_M-GGUF
+This model was converted to GGUF format from [`ibm-granite/granite-3.0-3b-a800m-base`](https://huggingface.co/ibm-granite/granite-3.0-3b-a800m-base) 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/ibm-granite/granite-3.0-3b-a800m-base) 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 davelsphere/granite-3.0-3b-a800m-base-Q4_K_M-GGUF --hf-file granite-3.0-3b-a800m-base-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo davelsphere/granite-3.0-3b-a800m-base-Q4_K_M-GGUF --hf-file granite-3.0-3b-a800m-base-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 davelsphere/granite-3.0-3b-a800m-base-Q4_K_M-GGUF --hf-file granite-3.0-3b-a800m-base-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo davelsphere/granite-3.0-3b-a800m-base-Q4_K_M-GGUF --hf-file granite-3.0-3b-a800m-base-q4_k_m.gguf -c 2048
+```