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--- |
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language: |
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- en |
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license: mit |
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library_name: transformers |
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inference: |
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parameters: |
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max_new_tokens: 64 |
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do_sample: true |
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temperature: 0.1 |
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repetition_penalty: 10 |
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no_repeat_ngram_size: 4 |
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eta_cutoff: 0.0006 |
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renormalize_logits: true |
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widget: |
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- text: My name is El Microondas the Wise, and |
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example_title: El Microondas |
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- text: Kennesaw State University is a public |
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example_title: Kennesaw State University |
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- text: Bungie Studios is an American video game developer. They are most famous for |
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developing the award winning Halo series of video games. They also made Destiny. |
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The studio was founded |
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example_title: Bungie |
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- text: The Mona Lisa is a world-renowned painting created by |
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example_title: Mona Lisa |
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- text: The Harry Potter series, written by J.K. Rowling, begins with the book titled |
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example_title: Harry Potter Series |
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- text: 'Question: I have cities, but no houses. I have mountains, but no trees. I |
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have water, but no fish. What am I? |
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|
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Answer:' |
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example_title: Riddle |
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- text: The process of photosynthesis involves the conversion of |
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example_title: Photosynthesis |
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- text: Jane went to the store to buy some groceries. She picked up apples, oranges, |
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and a loaf of bread. When she got home, she realized she forgot |
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example_title: Story Continuation |
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- text: 'Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph, |
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and another train leaves Station B at 10:00 AM and travels at 80 mph, when will |
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they meet if the distance between the stations is 300 miles? |
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|
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To determine' |
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example_title: Math Problem |
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- text: In the context of computer programming, an algorithm is |
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example_title: Algorithm Definition |
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pipeline_tag: text-generation |
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datasets: |
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- kenhktsui/minipile_quality_score_v1 |
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- kenhktsui/simple_wikipedia_LM_quality_score_v1 |
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- kenhktsui/refinedweb-3m_quality_score_v1 |
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- kenhktsui/TM-DATA_quality_score_v1 |
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- kenhktsui/openwebtext_quality_score_v1 |
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tags: |
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- TensorBlock |
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- GGUF |
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base_model: kenhktsui/nano-phi-115M-v0.1 |
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model-index: |
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- name: nano-phi-115M-v0.1 |
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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: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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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: acc_norm |
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value: 21.93 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1 |
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name: Open 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: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 27.86 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1 |
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name: Open 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: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 25.34 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1 |
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name: Open 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: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 46 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1 |
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name: Open 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: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 50.83 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1 |
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name: Open 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: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 0 |
|
name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kenhktsui/nano-phi-115M-v0.1 |
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name: Open LLM Leaderboard |
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--- |
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|
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<div style="width: auto; margin-left: auto; margin-right: auto"> |
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<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
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</div> |
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<div style="display: flex; justify-content: space-between; width: 100%;"> |
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<div style="display: flex; flex-direction: column; align-items: flex-start;"> |
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<p style="margin-top: 0.5em; margin-bottom: 0em;"> |
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Feedback and support: TensorBlock's <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a> |
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</p> |
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</div> |
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</div> |
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|
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## kenhktsui/nano-phi-115M-v0.1 - GGUF |
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|
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This repo contains GGUF format model files for [kenhktsui/nano-phi-115M-v0.1](https://huggingface.co/kenhktsui/nano-phi-115M-v0.1). |
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|
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The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d). |
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|
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<div style="text-align: left; margin: 20px 0;"> |
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<a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;"> |
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Run them on the TensorBlock client using your local machine ↗ |
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</a> |
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</div> |
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|
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## Prompt template |
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``` |
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|
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``` |
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|
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## Model file specification |
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|
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| Filename | Quant type | File Size | Description | |
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| -------- | ---------- | --------- | ----------- | |
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| [nano-phi-115M-v0.1-Q2_K.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q2_K.gguf) | Q2_K | 0.061 GB | smallest, significant quality loss - not recommended for most purposes | |
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| [nano-phi-115M-v0.1-Q3_K_S.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q3_K_S.gguf) | Q3_K_S | 0.067 GB | very small, high quality loss | |
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| [nano-phi-115M-v0.1-Q3_K_M.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q3_K_M.gguf) | Q3_K_M | 0.069 GB | very small, high quality loss | |
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| [nano-phi-115M-v0.1-Q3_K_L.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q3_K_L.gguf) | Q3_K_L | 0.072 GB | small, substantial quality loss | |
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| [nano-phi-115M-v0.1-Q4_0.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q4_0.gguf) | Q4_0 | 0.077 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
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| [nano-phi-115M-v0.1-Q4_K_S.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q4_K_S.gguf) | Q4_K_S | 0.077 GB | small, greater quality loss | |
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| [nano-phi-115M-v0.1-Q4_K_M.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q4_K_M.gguf) | Q4_K_M | 0.078 GB | medium, balanced quality - recommended | |
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| [nano-phi-115M-v0.1-Q5_0.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q5_0.gguf) | Q5_0 | 0.086 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
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| [nano-phi-115M-v0.1-Q5_K_S.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q5_K_S.gguf) | Q5_K_S | 0.086 GB | large, low quality loss - recommended | |
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| [nano-phi-115M-v0.1-Q5_K_M.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q5_K_M.gguf) | Q5_K_M | 0.087 GB | large, very low quality loss - recommended | |
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| [nano-phi-115M-v0.1-Q6_K.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q6_K.gguf) | Q6_K | 0.096 GB | very large, extremely low quality loss | |
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| [nano-phi-115M-v0.1-Q8_0.gguf](https://huggingface.co/tensorblock/nano-phi-115M-v0.1-GGUF/blob/main/nano-phi-115M-v0.1-Q8_0.gguf) | Q8_0 | 0.124 GB | very large, extremely low quality loss - not recommended | |
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## Downloading instruction |
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|
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### Command line |
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|
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Firstly, install Huggingface Client |
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|
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```shell |
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pip install -U "huggingface_hub[cli]" |
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``` |
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|
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Then, downoad the individual model file the a local directory |
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|
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```shell |
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huggingface-cli download tensorblock/nano-phi-115M-v0.1-GGUF --include "nano-phi-115M-v0.1-Q2_K.gguf" --local-dir MY_LOCAL_DIR |
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``` |
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If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try: |
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|
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```shell |
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huggingface-cli download tensorblock/nano-phi-115M-v0.1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
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``` |
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|
