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README.md

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+---
+base_model: eren23/DistiLabelOrca-TinyLLama-1.1B
+datasets:
+- argilla/distilabel-intel-orca-dpo-pairs
+language:
+- en
+library_name: transformers
+license: apache-2.0
+pipeline_tag: question-answering
+tags:
+- llama-cpp
+- gguf-my-repo
+model-index:
+- name: DistiLabelOrca-TinyLLama-1.1B
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 36.18
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/DistiLabelOrca-TinyLLama-1.1B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 61.15
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/DistiLabelOrca-TinyLLama-1.1B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 25.09
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/DistiLabelOrca-TinyLLama-1.1B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 38.05
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/DistiLabelOrca-TinyLLama-1.1B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 60.85
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/DistiLabelOrca-TinyLLama-1.1B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 1.67
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/DistiLabelOrca-TinyLLama-1.1B
+      name: Open LLM Leaderboard
+---
+
+# Solshine/DistiLabelOrca-TinyLLama-1.1B-Q4_K_M-GGUF
+This model was converted to GGUF format from [`eren23/DistiLabelOrca-TinyLLama-1.1B`](https://huggingface.co/eren23/DistiLabelOrca-TinyLLama-1.1B) 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/eren23/DistiLabelOrca-TinyLLama-1.1B) 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 Solshine/DistiLabelOrca-TinyLLama-1.1B-Q4_K_M-GGUF --hf-file distilabelorca-tinyllama-1.1b-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo Solshine/DistiLabelOrca-TinyLLama-1.1B-Q4_K_M-GGUF --hf-file distilabelorca-tinyllama-1.1b-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 Solshine/DistiLabelOrca-TinyLLama-1.1B-Q4_K_M-GGUF --hf-file distilabelorca-tinyllama-1.1b-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo Solshine/DistiLabelOrca-TinyLLama-1.1B-Q4_K_M-GGUF --hf-file distilabelorca-tinyllama-1.1b-q4_k_m.gguf -c 2048
+```