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+ ---
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+ language:
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+ - en
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+ - fr
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+ - ro
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+ - de
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+ - multilingual
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+ widget:
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+ - text: 'Translate to German: My name is Arthur'
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+ example_title: Translation
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+ - text: Please answer to the following question. Who is going to be the next Ballon
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+ d'or?
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+ example_title: Question Answering
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+ - text: 'Q: Can Geoffrey Hinton have a conversation with George Washington? Give the
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+ rationale before answering.'
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+ example_title: Logical reasoning
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+ - text: Please answer the following question. What is the boiling point of Nitrogen?
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+ example_title: Scientific knowledge
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+ - text: Answer the following yes/no question. Can you write a whole Haiku in a single
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+ tweet?
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+ example_title: Yes/no question
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+ - text: Answer the following yes/no question by reasoning step-by-step. Can you write
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+ a whole Haiku in a single tweet?
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+ example_title: Reasoning task
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+ - text: 'Q: ( False or not False or False ) is? A: Let''s think step by step'
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+ example_title: Boolean Expressions
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+ - text: The square root of x is the cube root of y. What is y to the power of 2, if
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+ x = 4?
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+ example_title: Math reasoning
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+ - text: 'Premise: At my age you will probably have learnt one lesson. Hypothesis: It''s
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+ not certain how many lessons you''ll learn by your thirties. Does the premise
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+ entail the hypothesis?'
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+ example_title: Premise and hypothesis
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+ tags:
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+ - text2text-generation
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+ - llama-cpp
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+ - gguf-my-repo
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+ datasets:
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+ - svakulenk0/qrecc
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+ - taskmaster2
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+ - djaym7/wiki_dialog
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+ - deepmind/code_contests
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+ - lambada
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+ - gsm8k
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+ - aqua_rat
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+ - esnli
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+ - quasc
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+ - qed
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+ license: apache-2.0
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+ base_model: google/flan-t5-large
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+ ---
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+
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+ # nguyenphuthien/flan-t5-large-Q4_K_M-GGUF
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+ This model was converted to GGUF format from [`google/flan-t5-large`](https://huggingface.co/google/flan-t5-large) 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/google/flan-t5-large) 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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+ ```
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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 nguyenphuthien/flan-t5-large-Q4_K_M-GGUF --hf-file flan-t5-large-q4_k_m.gguf -p "The meaning to life and the universe is"
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+ ```
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+
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+ ### Server:
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+ ```bash
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+ llama-server --hf-repo nguyenphuthien/flan-t5-large-Q4_K_M-GGUF --hf-file flan-t5-large-q4_k_m.gguf -c 2048
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+ ```
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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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+
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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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+
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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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+
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+ Step 3: Run inference through the main binary.
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+ ```
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+ ./llama-cli --hf-repo nguyenphuthien/flan-t5-large-Q4_K_M-GGUF --hf-file flan-t5-large-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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+ ./llama-server --hf-repo nguyenphuthien/flan-t5-large-Q4_K_M-GGUF --hf-file flan-t5-large-q4_k_m.gguf -c 2048
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+ ```