README.md

---
base_model: AI-MO/NuminaMath-7B-TIR
tags:
- alignment-handbook
- generated_from_trainer
- TensorBlock
- GGUF
widget:
- example_title: Math problem
  messages:
  - role: user
    content: For how many values of the constant $k$ will the polynomial $x^{2}+kx+36$
      have two distinct integer roots?
  output:
    text: "### Solution: \n1- For the polynomial \\\\( x^2 + kx + 36 \\\\) to have\
      \ two distinct integer roots, let's denote these roots by \\\\( r_1 \\\\) and\
      \ \\\\( r_2 \\\\).\n\n\n2- According to Vieta's formulas, the sum of the roots\
      \ \\\\( r_1 + r_2 \\\\) is equal to \\\\(-k\\\\), and the product of the roots\
      \ \\\\( r_1 \\\\cdot r_2 \\\\) is equal to 36.\n\n\n3- To find the distinct\
      \ integer pairs \\\\((r_1, r_2)\\\\) whose product is 36, we need to determine\
      \ all pairs of integers \\\\((r_1, r_2)\\\\) such that \\\\( r_1 \\\\cdot r_2\
      \ = 36 \\\\) and \\\\( r_1 \\\\neq r_2 \\\\).\n\n\n4- From the equation \\\\\
      ( r_1 + r_2 = -k \\\\), for each valid pair \\\\((r_1, r_2)\\\\), we can compute\
      \ the corresponding value of \\\\( k \\\\).\n\n\n5- Finally, since we need the\
      \ polynomial to have two distinct integer roots, we need to ensure that \\\\\
      ( r_1 \\\\) and \\\\( r_2 \\\\) are distinct.\nLet's start by finding all pairs\
      \ \\\\((r_1, r_2)\\\\) such that \\\\( r_1 \\\\cdot r_2 = 36 \\\\). We'll then\
      \ determine the values of \\\\( k \\\\) and ensure the roots are distinct.\n\
      ```python import itertools\n# Find all pairs (r1, r2) such that r1 * r2 = 36\
      \ product_36 = 36 factor_pairs = []\nfor i in range(1, product_36 + 1):\n  if\
      \ product_36 % i == 0:\n    pair = (i, product_36 // i)\n    if pair[0] != pair[1]:\
      \ # Ensure distinct pairs\n      factor_pairs.append(pair)\n    \n    # Calculate\
      \ k for each pair and ensure distinct integer roots\n    valid_k_values = set()\n\
      \    for r1, r2 in factor_pairs:\n      if r1 != r2:\n        k = -(r1 + r2)\n\
      \        valid_k_values.add(k)\n        \n    print((len(valid_k_values), sorted(valid_k_values)))\n\
      \ ```\n \n ```output\n (4, [-37, -20, -15,-13])\n ```\n The distinct integer\
      \ values of \\\\( k \\\\) that make the\npolynomial \\\\( x^2 + kx + 36 \\\\\
      ) have two distinct integer roots are \\\\(-37, -20, -15, \\\\text{and} -13\\\
      \\).\nTherefore, the number of such values of \\\\( k \\\\) is:\n[ \\\\boxed{4}\
      \ \\\\]"
pipeline_tag: text-generation
license: apache-2.0
model-index:
- name: NuminaMath-7B-TIR
  results: []
---

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## AI-MO/NuminaMath-7B-TIR - GGUF

This repo contains GGUF format model files for [AI-MO/NuminaMath-7B-TIR](https://huggingface.co/AI-MO/NuminaMath-7B-TIR).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).


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## Prompt template


```
### Problem: {prompt}
### Solution: 
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [NuminaMath-7B-TIR-Q2_K.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q2_K.gguf) | Q2_K | 2.532 GB | smallest, significant quality loss - not recommended for most purposes |
| [NuminaMath-7B-TIR-Q3_K_S.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q3_K_S.gguf) | Q3_K_S | 2.923 GB | very small, high quality loss |
| [NuminaMath-7B-TIR-Q3_K_M.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q3_K_M.gguf) | Q3_K_M | 3.223 GB | very small, high quality loss |
| [NuminaMath-7B-TIR-Q3_K_L.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q3_K_L.gguf) | Q3_K_L | 3.489 GB | small, substantial quality loss |
| [NuminaMath-7B-TIR-Q4_0.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q4_0.gguf) | Q4_0 | 3.725 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [NuminaMath-7B-TIR-Q4_K_S.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q4_K_S.gguf) | Q4_K_S | 3.749 GB | small, greater quality loss |
| [NuminaMath-7B-TIR-Q4_K_M.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q4_K_M.gguf) | Q4_K_M | 3.933 GB | medium, balanced quality - recommended |
| [NuminaMath-7B-TIR-Q5_0.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q5_0.gguf) | Q5_0 | 4.481 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [NuminaMath-7B-TIR-Q5_K_S.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q5_K_S.gguf) | Q5_K_S | 4.481 GB | large, low quality loss - recommended |
| [NuminaMath-7B-TIR-Q5_K_M.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q5_K_M.gguf) | Q5_K_M | 4.588 GB | large, very low quality loss - recommended |
| [NuminaMath-7B-TIR-Q6_K.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q6_K.gguf) | Q6_K | 5.284 GB | very large, extremely low quality loss |
| [NuminaMath-7B-TIR-Q8_0.gguf](https://huggingface.co/tensorblock/NuminaMath-7B-TIR-GGUF/blob/main/NuminaMath-7B-TIR-Q8_0.gguf) | Q8_0 | 6.842 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/NuminaMath-7B-TIR-GGUF --include "NuminaMath-7B-TIR-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/NuminaMath-7B-TIR-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```