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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - moe
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+ - frankenmoe
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+ - merge
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+ - mergekit
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+ - lazymergekit
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+ - TinyLlama/TinyLlama-1.1B-Chat-v1.0
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+ - vihangd/DopeyTinyLlama-1.1B-v1
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+ - cognitivecomputations/TinyDolphin-2.8.1-1.1b
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+ - Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test
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+ base_model:
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+ - TinyLlama/TinyLlama-1.1B-Chat-v1.0
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+ - vihangd/DopeyTinyLlama-1.1B-v1
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+ - cognitivecomputations/TinyDolphin-2.8.1-1.1b
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+ - Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test
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+ ---
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+
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+ # UltraCompute-7B-Base
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+
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+ UltraCompute-7B-Base is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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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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+
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+ ## 🧩 Configuration
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+
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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"
83
+ - "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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+
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+ ## 💻 Usage
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+
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+ ```python
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+ !pip install -qU transformers bitsandbytes accelerate
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+
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+ from transformers import AutoTokenizer
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+ import transformers
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+ import torch
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+
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+ model = "gmonsoon/UltraCompute-7B-Base"
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+
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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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+
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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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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
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+ "architectures": [
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+ "MixtralForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 2048,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 5632,
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+ "max_position_embeddings": 2048,
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+ "model_type": "mixtral",
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+ "num_attention_heads": 32,
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+ "num_experts_per_tok": 2,
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+ "num_hidden_layers": 22,
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+ "num_key_value_heads": 4,
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+ "num_local_experts": 4,
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+ "output_router_logits": false,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 10000.0,
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+ "router_aux_loss_coef": 0.001,
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+ "sliding_window": null,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float16",
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+ "transformers_version": "4.37.2",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
mergekit_moe_config.yml ADDED
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+
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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."
10
+ - "Optimize this C# script."
11
+ - "Implement this feature using JavaScript."
12
+ - "Convert this HTML structure into a more efficient design."
13
+ - "Assist me with writing a program that"
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+ - source_model: vihangd/DopeyTinyLlama-1.1B-v1
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+ positive_prompts:
16
+ - "How do you"
17
+ - "Explain the concept of"
18
+ - "Give an overview of"
19
+ - "Compare and contrast between"
20
+ - "Provide information about"
21
+ - "Help me understand"
22
+ - "Summarize"
23
+ - "Make a recommendation on"
24
+ - "Answer this question"
25
+ - 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"
28
+ - "Modify this function to improve its performance"
29
+ - "Refactor this code to enhance readability"
30
+ - "Create a custom function for this specific use case"
31
+ - "Optimize this algorithm to reduce computational complexity"
32
+ - "Implement this feature by extending existing codebase"
33
+ - "Integrate this API call into the application"
34
+ - "Help me troubleshoot and fix this bug"
35
+ - "Review and test this code snippet before deployment"
36
+ - "Analyze this error log to identify potential issues"
37
+ - "Generate a set of unit tests for this module"
38
+ - "Evaluate different approaches to solving this problem"
39
+ - "Do a web search for"
40
+ - "Use the plugin to"
41
+ - source_model: Josephgflowers/Tinyllama-Cinder-1.3B-Reason-Test
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+ positive_prompts:
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+ - "add these numbers"
44
+ - "whats 2+2"
45
+ - "subtraction"
46
+ - "division"
47
+ - "multiplication"
48
+ - "addition"
49
+ - "I need help with a math problem"
50
+ - "Solve for x"
51
+ - "Add these two numbers together: 4 + 3 = 7"
52
+ - "Multiply 5 by 6: 5 * 6 = 30"
53
+ - "Divide 8 by 2: 8 / 2 = 4"
54
+ - "Find the remainder when 9 is divided by 3: 9 % 3 = 0"
55
+ - "Calculate the square root of 16: sqrt(16) = 4"
56
+ - "Simplify the expression (a+b)/(c-d): (a+b)/(c-d)"
57
+ - "Factor out the common factor of 2 from 4x + 6y: 2(2x + 3y)"
58
+ - "Solve for x in the equation 3x - 7 = 2x + 5: x = 12"
59
+ - "Graph the line y = 2x + 3"
60
+ - "Approximate pi to three decimal places: 3.142"
61
+ - "Find the derivative of f(x) = sin(x): f'(x) = cos(x)"
62
+ - "Integrate g(x) = x^2 over the interval [0, 1]: g(1) - g(0) = 1/3"
63
+ - "Calculate the determinant of the matrix A = [[2, 3], [4, 5]]: det(A) = 2*5 - 3*4 = -2"
64
+ - "Solve the system of equations Ax = b: x = [-5, 10]"
65
+ - "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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