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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- llama-cpp |
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- gguf-my-repo |
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base_model: cognitivecomputations/TinyDolphin-2.8.1-1.1b |
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datasets: |
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- cerebras/SlimPajama-627B |
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- bigcode/starcoderdata |
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- teknium/openhermes |
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--- |
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# v8karlo/TinyDolphin-2.8.1-1.1b-Q4_K_M-GGUF |
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UNCENSORED model. |
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In order to make your GGUF file type go to original Tiny Dolphin repo. |
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https://huggingface.co/cognitivecomputations/TinyDolphin-2.8-1.1b?text=My+name+is+Teven+and+I+am+a+20-year-old+college+student+from+the+University+of+Kansas.+I+have+a+passion . |
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Copy name of the model TinyDolphin-2.8-1.1b. |
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Go to Convert-to-GGUF repo https://huggingface.co/spaces/ggml-org/gguf-my-repo and paste model name into Hub Model ID field, choose Quantization Method and press Submit button. |
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This model was converted to GGUF format from [`cognitivecomputations/TinyDolphin-2.8.1-1.1b`](https://huggingface.co/cognitivecomputations/TinyDolphin-2.8.1-1.1b) 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/cognitivecomputations/TinyDolphin-2.8.1-1.1b) for more details on the model. |
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Convert Safetensors to GGUF . |
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https://huggingface.co/spaces/ggml-org/gguf-my-repo . |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/662c3116277765660783ca6d/NhfH9cw1jZ77FeQV6EFT9.png) |
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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 --hf-repo v8karlo/TinyDolphin-2.8.1-1.1b-Q4_K_M-GGUF --hf-file tinydolphin-2.8.1-1.1b-q4_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 v8karlo/TinyDolphin-2.8.1-1.1b-Q4_K_M-GGUF --hf-file tinydolphin-2.8.1-1.1b-q4_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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./main --hf-repo v8karlo/TinyDolphin-2.8.1-1.1b-Q4_K_M-GGUF --hf-file tinydolphin-2.8.1-1.1b-q4_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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./server --hf-repo v8karlo/TinyDolphin-2.8.1-1.1b-Q4_K_M-GGUF --hf-file tinydolphin-2.8.1-1.1b-q4_k_m.gguf -c 2048 |
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``` |
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