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--- |
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base_model: adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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datasets: |
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- adalbertojunior/dolphin_portuguese_legal |
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language: |
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- pt |
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library_name: transformers |
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tags: |
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- llama-cpp |
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- gguf-my-repo |
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model-index: |
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- name: Llama-3-8B-Dolphin-Portuguese-v0.3 |
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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: ENEM Challenge (No Images) |
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type: eduagarcia/enem_challenge |
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split: train |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc |
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value: 68.86 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese 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: BLUEX (No Images) |
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type: eduagarcia-temp/BLUEX_without_images |
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split: train |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc |
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value: 57.86 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese 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: OAB Exams |
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type: eduagarcia/oab_exams |
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split: train |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc |
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value: 61.91 |
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name: accuracy |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese 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: Assin2 RTE |
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type: assin2 |
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split: test |
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args: |
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num_few_shot: 15 |
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metrics: |
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- type: f1_macro |
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value: 93.05 |
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name: f1-macro |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese 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: Assin2 STS |
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type: eduagarcia/portuguese_benchmark |
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split: test |
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args: |
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num_few_shot: 15 |
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metrics: |
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- type: pearson |
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value: 76.48 |
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name: pearson |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese 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: FaQuAD NLI |
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type: ruanchaves/faquad-nli |
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split: test |
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args: |
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num_few_shot: 15 |
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metrics: |
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- type: f1_macro |
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value: 76.78 |
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name: f1-macro |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese 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: HateBR Binary |
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type: ruanchaves/hatebr |
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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: f1_macro |
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value: 83.25 |
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name: f1-macro |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese 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: PT Hate Speech Binary |
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type: hate_speech_portuguese |
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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: f1_macro |
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value: 68.85 |
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name: f1-macro |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese 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: tweetSentBR |
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type: eduagarcia/tweetsentbr_fewshot |
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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: f1_macro |
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value: 71.3 |
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name: f1-macro |
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source: |
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url: https://huggingface.co./spaces/eduagarcia/open_pt_llm_leaderboard?query=adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3 |
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name: Open Portuguese LLM Leaderboard |
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--- |
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|
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# brazilianslib/Llama-3-8B-Dolphin-Portuguese-v0.3-Q8_0-GGUF |
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This model was converted to GGUF format from [`adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3`](https://huggingface.co./adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3) 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./adalbertojunior/Llama-3-8B-Dolphin-Portuguese-v0.3) for more details on the model. |
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|
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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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|
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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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|
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### CLI: |
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```bash |
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llama-cli --hf-repo brazilianslib/Llama-3-8B-Dolphin-Portuguese-v0.3-Q8_0-GGUF --hf-file llama-3-8b-dolphin-portuguese-v0.3-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 brazilianslib/Llama-3-8B-Dolphin-Portuguese-v0.3-Q8_0-GGUF --hf-file llama-3-8b-dolphin-portuguese-v0.3-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 brazilianslib/Llama-3-8B-Dolphin-Portuguese-v0.3-Q8_0-GGUF --hf-file llama-3-8b-dolphin-portuguese-v0.3-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 brazilianslib/Llama-3-8B-Dolphin-Portuguese-v0.3-Q8_0-GGUF --hf-file llama-3-8b-dolphin-portuguese-v0.3-q8_0.gguf -c 2048 |
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``` |
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