3f49da36eb
Model: kenonix/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k-Q8_0-GGUF Source: Original Platform
96 lines
2.6 KiB
Markdown
96 lines
2.6 KiB
Markdown
---
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license: apache-2.0
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datasets:
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- TeichAI/gemini-2.5-flash-11000x
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base_model: DavidAU/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k
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language:
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- en
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- fr
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- de
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- es
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- it
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- pt
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- zh
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- ja
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- ru
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- ko
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tags:
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- thinking
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- reasoning
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- Gemini Flash
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- creative
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- creative writing
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- fiction writing
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- plot generation
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- sub-plot generation
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- story generation
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- scene continue
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- storytelling
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- fiction story
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- science fiction
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- romance
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- all genres
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- story
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- writing
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- vivid prosing
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- vivid writing
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- fiction
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- roleplaying
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- bfloat16
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- role play
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- 128k context
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- llama3.3
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- llama-3
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- llama-3.3
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- unsloth
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- finetune
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- llama-cpp
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- gguf-my-repo
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pipeline_tag: text-generation
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library_name: transformers
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---
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# kenonix/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k-Q8_0-GGUF
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This model was converted to GGUF format from [`DavidAU/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k`](https://huggingface.co/DavidAU/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k) 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/DavidAU/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k) 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 kenonix/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k-Q8_0-GGUF --hf-file llama-3.3-8b-thinking-gemini-flash-11000x-128k-q8_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 kenonix/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k-Q8_0-GGUF --hf-file llama-3.3-8b-thinking-gemini-flash-11000x-128k-q8_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 kenonix/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k-Q8_0-GGUF --hf-file llama-3.3-8b-thinking-gemini-flash-11000x-128k-q8_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 kenonix/Llama-3.3-8B-Thinking-Gemini-Flash-11000x-128k-Q8_0-GGUF --hf-file llama-3.3-8b-thinking-gemini-flash-11000x-128k-q8_0.gguf -c 2048
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```
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