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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- moe |
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- merge |
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- mergekit |
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model-index: |
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- name: TinyUltra-4x1.1B-Base-Alpha |
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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: 34.9 |
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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=indischepartij/TinyUltra-4x1.1B-Base-Alpha |
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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: 61.42 |
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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=indischepartij/TinyUltra-4x1.1B-Base-Alpha |
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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: 25.42 |
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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=indischepartij/TinyUltra-4x1.1B-Base-Alpha |
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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: 37.59 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=indischepartij/TinyUltra-4x1.1B-Base-Alpha |
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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: 65.75 |
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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=indischepartij/TinyUltra-4x1.1B-Base-Alpha |
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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: 2.58 |
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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=indischepartij/TinyUltra-4x1.1B-Base-Alpha |
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name: Open LLM Leaderboard |
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--- |
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# TinyUltra-4x1.1B-Base-Alpha |
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TinyUltra-4x1.1B-Base-Alpha is a Mixure of Experts (MoE) made with the following models using MergeKit: |
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* [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) |
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* [vihangd/DopeyTinyLlama-1.1B-v1](https://huggingface.co/vihangd/DopeyTinyLlama-1.1B-v1) |
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* [cognitivecomputations/TinyDolphin-2.8.1-1.1b](https://huggingface.co/cognitivecomputations/TinyDolphin-2.8.1-1.1b) |
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* [Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test](https://huggingface.co/Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test) |
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# Modelfile/Prompt format |
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```markdown |
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SYSTEM You are a TinyUltra, helpful and lovely AI assistant. |
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TEMPLATE <|system|> {{ .System }}</s> <|user|> {{ .Prompt }}</s> <|assistant|> |
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PARAMETER stop <|system|> |
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PARAMETER stop <|user|> |
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PARAMETER stop <|assistant|> |
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PARAMETER stop </s> |
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``` |
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## 🧩 Configuration |
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```yaml |
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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gate_mode: hidden |
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dtype: float16 |
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experts: |
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- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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positive_prompts: |
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- "Help me debug this code." |
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- "Rewrite this function in Python." |
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- "Optimize this C# script." |
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- "Implement this feature using JavaScript." |
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- "Convert this HTML structure into a more efficient design." |
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- "Assist me with writing a program that" |
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- source_model: vihangd/DopeyTinyLlama-1.1B-v1 |
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positive_prompts: |
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- "How do you" |
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- "Explain the concept of" |
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- "Give an overview of" |
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- "Compare and contrast between" |
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- "Provide information about" |
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- "Help me understand" |
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- "Summarize" |
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- "Make a recommendation on" |
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- "Answer this question" |
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- source_model: cognitivecomputations/TinyDolphin-2.8.1-1.1b |
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positive_prompts: |
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- "Write a program to solve this problem" |
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- "Modify this function to improve its performance" |
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- "Refactor this code to enhance readability" |
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- "Create a custom function for this specific use case" |
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- "Optimize this algorithm to reduce computational complexity" |
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- "Implement this feature by extending existing codebase" |
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- "Integrate this API call into the application" |
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- "Help me troubleshoot and fix this bug" |
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- "Review and test this code snippet before deployment" |
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- "Analyze this error log to identify potential issues" |
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- "Generate a set of unit tests for this module" |
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- "Evaluate different approaches to solving this problem" |
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- "Do a web search for" |
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- "Use the plugin to" |
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- source_model: Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test |
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positive_prompts: |
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- "add these numbers" |
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- "whats 2+2" |
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- "subtraction" |
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- "division" |
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- "multiplication" |
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- "addition" |
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- "I need help with a math problem" |
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- "Solve for x" |
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- "Add these two numbers together: 4 + 3 = 7" |
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- "Multiply 5 by 6: 5 * 6 = 30" |
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- "Divide 8 by 2: 8 / 2 = 4" |
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- "Find the remainder when 9 is divided by 3: 9 % 3 = 0" |
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- "Calculate the square root of 16: sqrt(16) = 4" |
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- "Simplify the expression (a+b)/(c-d): (a+b)/(c-d)" |
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- "Factor out the common factor of 2 from 4x + 6y: 2(2x + 3y)" |
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- "Solve for x in the equation 3x - 7 = 2x + 5: x = 12" |
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- "Graph the line y = 2x + 3" |
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- "Approximate pi to three decimal places: 3.142" |
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- "Find the derivative of f(x) = sin(x): f'(x) = cos(x)" |
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- "Integrate g(x) = x^2 over the interval [0, 1]: g(1) - g(0) = 1/3" |
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- "Calculate the determinant of the matrix A = [[2, 3], [4, 5]]: det(A) = 2*5 - 3*4 = -2" |
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- "Solve the system of equations Ax = b: x = [-5, 10]" |
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- "Calculate the sum of the first n natural numbers using the formula Sn = n*(n+1)/2: sum(n=1 to 5) = 15" |
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``` |
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## 💻 Usage |
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```python |
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!pip install -qU transformers bitsandbytes accelerate |
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from transformers import AutoTokenizer |
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import transformers |
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import torch |
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model = "gmonsoon/TinyUltra-4x1.1B-Base-Alpha" |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, |
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) |
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] |
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
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GGUF: https://huggingface.co/indischepartij/TinyUltra-4x1.1B-Base-Alpha-GGUF |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_indischepartij__TinyUltra-4x1.1B-Base-Alpha) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |37.94| |
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|AI2 Reasoning Challenge (25-Shot)|34.90| |
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|HellaSwag (10-Shot) |61.42| |
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|MMLU (5-Shot) |25.42| |
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|TruthfulQA (0-shot) |37.59| |
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|Winogrande (5-shot) |65.75| |
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|GSM8k (5-shot) | 2.58| |
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