metadata
license: llama2
datasets:
- gsm8k
- competition_math
language:
- en
metrics:
- exact_match
library_name: transformers
pipeline_tag: text-generation
tags:
- code
- math
- TensorBlock
- GGUF
base_model: llm-agents/tora-code-7b-v1.0
llm-agents/tora-code-7b-v1.0 - GGUF
This repo contains GGUF format model files for llm-agents/tora-code-7b-v1.0.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.
Our projects
| Forge | |
|---|---|
|
|
| An OpenAI-compatible multi-provider routing layer. | |
| π Try it now! π | |
| Awesome MCP Servers | TensorBlock Studio |
![]() |
![]() |
| A comprehensive collection of Model Context Protocol (MCP) servers. | A lightweight, open, and extensible multi-LLM interaction studio. |
| π See what we built π | π See what we built π |
Prompt template
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| tora-code-7b-v1.0-Q2_K.gguf | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes |
| tora-code-7b-v1.0-Q3_K_S.gguf | Q3_K_S | 2.948 GB | very small, high quality loss |
| tora-code-7b-v1.0-Q3_K_M.gguf | Q3_K_M | 3.298 GB | very small, high quality loss |
| tora-code-7b-v1.0-Q3_K_L.gguf | Q3_K_L | 3.597 GB | small, substantial quality loss |
| tora-code-7b-v1.0-Q4_0.gguf | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| tora-code-7b-v1.0-Q4_K_S.gguf | Q4_K_S | 3.857 GB | small, greater quality loss |
| tora-code-7b-v1.0-Q4_K_M.gguf | Q4_K_M | 4.081 GB | medium, balanced quality - recommended |
| tora-code-7b-v1.0-Q5_0.gguf | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| tora-code-7b-v1.0-Q5_K_S.gguf | Q5_K_S | 4.652 GB | large, low quality loss - recommended |
| tora-code-7b-v1.0-Q5_K_M.gguf | Q5_K_M | 4.783 GB | large, very low quality loss - recommended |
| tora-code-7b-v1.0-Q6_K.gguf | Q6_K | 5.529 GB | very large, extremely low quality loss |
| tora-code-7b-v1.0-Q8_0.gguf | Q8_0 | 7.161 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/llm-agents_tora-code-7b-v1.0-GGUF --include "tora-code-7b-v1.0-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:
huggingface-cli download tensorblock/llm-agents_tora-code-7b-v1.0-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'

