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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- text-generation |
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- TensorBlock |
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- GGUF |
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base_model: Felladrin/Smol-Llama-101M-Chat-v1 |
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datasets: |
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- Open-Orca/SlimOrca-Dedup |
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- VMware/open-instruct |
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- LDJnr/Capybara |
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- cognitivecomputations/ultrachat-uncensored |
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- starfishmedical/webGPT_x_dolly |
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- THUDM/webglm-qa |
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widget: |
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- messages: |
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- role: system |
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content: You are a helpful assistant who gives creative responses. |
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- role: user |
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content: Write the background story of a game about wizards and llamas in a sci-fi |
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world. |
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- messages: |
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- role: system |
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content: A friendly chat between a user and an assistant. |
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- role: user |
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content: Got a question for you! |
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- role: assistant |
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content: Sure! What's it? |
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- role: user |
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content: I need to build a simple website. Where should I start learning about |
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web development? |
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- messages: |
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- role: system |
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content: You are a helpful assistant who provides concise answers to the user's |
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questions. |
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- role: user |
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content: How to become more healthy? |
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- messages: |
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- role: system |
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content: You are a helpful assistant, who always answers with empathy. |
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- role: user |
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content: List the pros and cons of social media. |
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- messages: |
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- role: system |
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content: You are a helpful assistant, who always answers with empathy. |
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- role: user |
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content: Hello! |
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- role: assistant |
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content: Hi! How can I help you today? |
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- role: user |
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content: 'Take a look at the info below. |
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|
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- The tape inside the VHS cassettes is very delicate and can be easily ruined, |
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making them unplayable and unrepairable. The reason the tape deteriorates is |
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that the magnetic charge needed for them to work is not permanent, and the magnetic |
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particles end up losing their charge in a process known as remanence decay. |
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These particles could also become demagnetised via being stored too close to |
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a magnetic source. |
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|
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- One of the most significant issues with VHS tapes is that they have moving |
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parts, meaning that there are more occasions when something can go wrong, damaging |
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your footage or preventing it from playing back. The tape itself is a prominent |
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cause of this, and tape slippage can occur. Tapes slippage can be caused when |
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the tape loses its tension, or it has become warped. These problems can occur |
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in storage due to high temperatures or frequent changes in humidity. |
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|
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- VHS tapes deteriorate over time from infrequent or overuse. Neglect means |
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mold and dirt, while overuse can lead to scratches and technical difficulties. |
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This is why old VHS tapes inevitably experience malfunctions after a long period |
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of time. Usually anywhere between 10 to 25+ years. |
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|
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- Some VHS tapes like newer mini DVs and Digital 8 tapes can suffer from digital |
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corruption, meaning that the footage becomes lost and cannot be recovered. These |
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tapes were the steppingstone from VHS to the digital age when capturing footage |
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straight to digital became the norm. Unfortunately,they are susceptible to digital |
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corruption, which causes video pixilation and/or loss of audio.' |
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- role: assistant |
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content: Alright! |
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- role: user |
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content: 'Now I''m going to write my question, and if the info above is useful, |
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you can use them in your response. |
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Ready?' |
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- role: assistant |
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content: Ready for your question! |
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- role: user |
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content: Why do VHS tapes deteriorate over time? |
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inference: |
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parameters: |
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max_new_tokens: 250 |
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penalty_alpha: 0.5 |
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top_k: 4 |
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repetition_penalty: 1.105 |
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model-index: |
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- name: Smol-Llama-101M-Chat-v1 |
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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: 22.87 |
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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=Felladrin/Smol-Llama-101M-Chat-v1 |
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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: 28.69 |
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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=Felladrin/Smol-Llama-101M-Chat-v1 |
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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: 24.93 |
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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=Felladrin/Smol-Llama-101M-Chat-v1 |
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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: 45.76 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Smol-Llama-101M-Chat-v1 |
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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: 50.04 |
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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=Felladrin/Smol-Llama-101M-Chat-v1 |
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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: 0.08 |
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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=Felladrin/Smol-Llama-101M-Chat-v1 |
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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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## Felladrin/Smol-Llama-101M-Chat-v1 - GGUF |
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This repo contains GGUF format model files for [Felladrin/Smol-Llama-101M-Chat-v1](https://huggingface.co/Felladrin/Smol-Llama-101M-Chat-v1). |
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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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<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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## Prompt template |
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``` |
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<|im_start|>system |
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{system_prompt}<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant |
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``` |
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## Model file specification |
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| Filename | Quant type | File Size | Description | |
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| -------- | ---------- | --------- | ----------- | |
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| [Smol-Llama-101M-Chat-v1-Q2_K.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q2_K.gguf) | Q2_K | 0.048 GB | smallest, significant quality loss - not recommended for most purposes | |
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| [Smol-Llama-101M-Chat-v1-Q3_K_S.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q3_K_S.gguf) | Q3_K_S | 0.054 GB | very small, high quality loss | |
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| [Smol-Llama-101M-Chat-v1-Q3_K_M.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q3_K_M.gguf) | Q3_K_M | 0.056 GB | very small, high quality loss | |
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| [Smol-Llama-101M-Chat-v1-Q3_K_L.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q3_K_L.gguf) | Q3_K_L | 0.059 GB | small, substantial quality loss | |
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| [Smol-Llama-101M-Chat-v1-Q4_0.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q4_0.gguf) | Q4_0 | 0.064 GB | legacy; small, very high quality loss - prefer using Q3_K_M | |
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| [Smol-Llama-101M-Chat-v1-Q4_K_S.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q4_K_S.gguf) | Q4_K_S | 0.064 GB | small, greater quality loss | |
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| [Smol-Llama-101M-Chat-v1-Q4_K_M.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q4_K_M.gguf) | Q4_K_M | 0.065 GB | medium, balanced quality - recommended | |
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| [Smol-Llama-101M-Chat-v1-Q5_0.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q5_0.gguf) | Q5_0 | 0.074 GB | legacy; medium, balanced quality - prefer using Q4_K_M | |
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| [Smol-Llama-101M-Chat-v1-Q5_K_S.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q5_K_S.gguf) | Q5_K_S | 0.074 GB | large, low quality loss - recommended | |
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| [Smol-Llama-101M-Chat-v1-Q5_K_M.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q5_K_M.gguf) | Q5_K_M | 0.074 GB | large, very low quality loss - recommended | |
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| [Smol-Llama-101M-Chat-v1-Q6_K.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q6_K.gguf) | Q6_K | 0.084 GB | very large, extremely low quality loss | |
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| [Smol-Llama-101M-Chat-v1-Q8_0.gguf](https://huggingface.co/tensorblock/Smol-Llama-101M-Chat-v1-GGUF/blob/main/Smol-Llama-101M-Chat-v1-Q8_0.gguf) | Q8_0 | 0.108 GB | very large, extremely low quality loss - not recommended | |
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## Downloading instruction |
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### Command line |
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Firstly, install Huggingface Client |
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```shell |
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pip install -U "huggingface_hub[cli]" |
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``` |
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Then, downoad the individual model file the a local directory |
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```shell |
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huggingface-cli download tensorblock/Smol-Llama-101M-Chat-v1-GGUF --include "Smol-Llama-101M-Chat-v1-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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```shell |
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huggingface-cli download tensorblock/Smol-Llama-101M-Chat-v1-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf' |
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``` |
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