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README.md
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1 |
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---
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2 |
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base_model: LeroyDyer/LCARS_AI_DeepMind
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datasets:
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+
- gretelai/synthetic_text_to_sql
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+
- HuggingFaceTB/cosmopedia
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+
- teknium/OpenHermes-2.5
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7 |
+
- Open-Orca/SlimOrca
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8 |
+
- Open-Orca/OpenOrca
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9 |
+
- cognitivecomputations/dolphin-coder
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10 |
+
- databricks/databricks-dolly-15k
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11 |
+
- yahma/alpaca-cleaned
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12 |
+
- uonlp/CulturaX
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13 |
+
- mwitiderrick/SwahiliPlatypus
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14 |
+
- swahili
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15 |
+
- Rogendo/English-Swahili-Sentence-Pairs
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16 |
+
- ise-uiuc/Magicoder-Evol-Instruct-110K
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+
- meta-math/MetaMathQA
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+
- abacusai/ARC_DPO_FewShot
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+
- abacusai/MetaMath_DPO_FewShot
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+
- abacusai/HellaSwag_DPO_FewShot
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+
- HaltiaAI/Her-The-Movie-Samantha-and-Theodore-Dataset
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+
- gretelai/synthetic_text_to_sql
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+
- HuggingFaceTB/cosmopedia
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- teknium/OpenHermes-2.5
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+
- cognitivecomputations/dolphin-coder
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+
- databricks/databricks-dolly-15k
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+
- yahma/alpaca-cleaned
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28 |
+
- uonlp/CulturaX
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+
- mwitiderrick/SwahiliPlatypus
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+
- swahili
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31 |
+
- Rogendo/English-Swahili-Sentence-Pairs
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+
- ise-uiuc/Magicoder-Evol-Instruct-110K
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33 |
+
- meta-math/MetaMathQA
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language:
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35 |
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- en
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license: apache-2.0
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metrics:
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- accuracy
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+
- bertscore
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+
- bleu
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+
- brier_score
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- cer
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+
- character
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- charcut_mt
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- chrf
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- code_eval
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tags:
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48 |
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- text-generation-inference
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+
- transformers
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- leaderboard
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+
- mistral
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- trl
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53 |
+
- llama-cpp
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54 |
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- gguf-my-repo
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+
y-Gene:
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56 |
+
- LeroyDyer/Mixtral_AI_DeepMind
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57 |
+
- LeroyDyer/Mixtral_AI_CyberUltron_DPO
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58 |
+
- LeroyDyer/Mixtral_AI_Chat_2.0
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+
- LeroyDyer/Mixtral_AI_DeepMedicalMind
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60 |
+
- LeroyDyer/Mixtral_AI_Samantha
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+
x-Gene:
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- LeroyDyer/Mixtral_AI_Chat_2.0
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- LeroyDyer/Mixtral_BioMedical
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- LeroyDyer/Mixtral_AI_Medic
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+
- LeroyDyer/Mixtral_Cyber_BioMedic
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- LeroyDyer/Mixtral_AI_DeepMedicalMind
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+
Variant:
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- LeroyDyer/MetaMath_LLM
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- LeroyDyer/TruthfulQA_LLM
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- LeroyDyer/HellaSwag_LLM
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- LeroyDyer/Mixtral_AI_DeepMedicalMind
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model-index:
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- name: Mixtral_AI_CyberTron_DeepMind_III_UFT
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 61.86
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name: normalized accuracy
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source:
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+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LeroyDyer/Mixtral_AI_CyberTron_DeepMind_III_UFT
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name: Open LLM Leaderboard
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+
- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 83.15
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LeroyDyer/Mixtral_AI_CyberTron_DeepMind_III_UFT
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 61.95
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LeroyDyer/Mixtral_AI_CyberTron_DeepMind_III_UFT
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 49.41
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LeroyDyer/Mixtral_AI_CyberTron_DeepMind_III_UFT
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name: Open LLM Leaderboard
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+
- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 77.98
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+
name: accuracy
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+
source:
|
156 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LeroyDyer/Mixtral_AI_CyberTron_DeepMind_III_UFT
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name: Open LLM Leaderboard
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+
- task:
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159 |
+
type: text-generation
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160 |
+
name: Text Generation
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161 |
+
dataset:
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162 |
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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+
value: 51.86
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+
name: accuracy
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+
source:
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+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=LeroyDyer/Mixtral_AI_CyberTron_DeepMind_III_UFT
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name: Open LLM Leaderboard
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---
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+
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# victorbur/LCARS_AI_DeepMind-Q5_K_M-GGUF
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This model was converted to GGUF format from [`LeroyDyer/LCARS_AI_DeepMind`](https://huggingface.co/LeroyDyer/LCARS_AI_DeepMind) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/LeroyDyer/LCARS_AI_DeepMind) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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```bash
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brew install llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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### CLI:
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```bash
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llama-cli --hf-repo victorbur/LCARS_AI_DeepMind-Q5_K_M-GGUF --hf-file lcars_ai_deepmind-q5_k_m.gguf -p "The meaning to life and the universe is"
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```
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### Server:
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```bash
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llama-server --hf-repo victorbur/LCARS_AI_DeepMind-Q5_K_M-GGUF --hf-file lcars_ai_deepmind-q5_k_m.gguf -c 2048
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```
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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.
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Step 1: Clone llama.cpp from GitHub.
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```
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git clone https://github.com/ggerganov/llama.cpp
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```
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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).
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```
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cd llama.cpp && LLAMA_CURL=1 make
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```
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Step 3: Run inference through the main binary.
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```
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./llama-cli --hf-repo victorbur/LCARS_AI_DeepMind-Q5_K_M-GGUF --hf-file lcars_ai_deepmind-q5_k_m.gguf -p "The meaning to life and the universe is"
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```
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or
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```
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./llama-server --hf-repo victorbur/LCARS_AI_DeepMind-Q5_K_M-GGUF --hf-file lcars_ai_deepmind-q5_k_m.gguf -c 2048
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```
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