70 lines
1.8 KiB
Markdown
70 lines
1.8 KiB
Markdown
---
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- text-generation-inference
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- code
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- Hitesh_V_Founder
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- https://chat.hyze.dev
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- llama-cpp
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- gguf-my-repo
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base_model: HyzeAI/HyzeMini
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---
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<p align="center">
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<img src="https://i.imgur.com/ePJMLNp.png" alt="Hyze Logo" width="405"/>
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</p>
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<h1 align="center">HyzeMini</h1>
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<p align="center">
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A quantized lightweight text-generation model by <b>Hyze AI</b>
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</p>
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<p align="center">
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🔗 <a href="https://chat.hyze.dev">Chat with all models</a> •
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📘 <a href="https://academy.hyze.dev">HyzeAcademy</a> •
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🧠 <a href="https://note.hyze.dev">HyzeNote (NotebookLM alternate)</a>
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</p>
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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 HyzeAI/HyzeMini-Q4_0-GGUF --hf-file hyzemini-q4_0.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 HyzeAI/HyzeMini-Q4_0-GGUF --hf-file hyzemini-q4_0.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 HyzeAI/HyzeMini-Q4_0-GGUF --hf-file hyzemini-q4_0.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 HyzeAI/HyzeMini-Q4_0-GGUF --hf-file hyzemini-q4_0.gguf -c 2048
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```
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