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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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# 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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## 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 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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### 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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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 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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``` |
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