AncientCatz
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README.md
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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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tags:
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- text2text-generation
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- llama-cpp
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- gguf-my-repo
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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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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-small
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---
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# AncientCatz/flan-t5-small-Q2_K-GGUF
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This model was converted to GGUF format from [`google/flan-t5-small`](https://huggingface.co/google/flan-t5-small) 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-small) 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 AncientCatz/flan-t5-small-Q2_K-GGUF --hf-file flan-t5-small-q2_k.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 AncientCatz/flan-t5-small-Q2_K-GGUF --hf-file flan-t5-small-q2_k.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 AncientCatz/flan-t5-small-Q2_K-GGUF --hf-file flan-t5-small-q2_k.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 AncientCatz/flan-t5-small-Q2_K-GGUF --hf-file flan-t5-small-q2_k.gguf -c 2048
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```
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