groxaxo/MagiSeek-V1.1-GGUF

🤗 Hugging Face 来源text-generationapache-2.075 GBGGUF✓ 4 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo groxaxo/MagiSeek-V1.1-GGUF ./model-folder
需要做种者 →

MagiSeek V1.1 GGUF

Overview

MagiSeek-V1.1-GGUF is a GGUF release for llama.cpp-compatible runtimes and local inference, published by groxaxo. It is intended for open-source evaluation, reproducible experimentation, and compatible local or hosted inference workflows. The wording below is deliberately limited to what can be verified from this repository's metadata and artifacts.

At a glance

Field Details
Format GGUF
Source / base groxaxo/MagiSeek-V1.1
Intended task text-generation
License apache-2.0

What is included

  • *.gguf (4 files)
  • Additional configuration, tokenizer, processor, or shard files (4 visible artifacts total)

Quick start

llama.cpp

Download a .gguf file that fits your available memory, then run it with a current llama.cpp build:

llama-cli \
  -m /path/to/model.gguf \
  -p "Write a concise technical summary."

For vision or any-to-any models, download the matching multimodal projection file when one is provided and follow the source model's modality-specific instructions.

Compatibility and responsible use

  • Use a runtime that explicitly supports this format, architecture, and modality.
  • Keep configuration, tokenizer, processor, projection, and weight files from the same revision together.
  • Review the source model card and license before redistribution or deployment.
  • Hardware needs depend on parameter count, context length, cache precision, quantization, and concurrency.
  • Report reproducible issues with the runtime version, hardware, launch command, and a minimal example.

Quantization or conversion changes numerical behavior, memory use, and throughput relative to the source checkpoint; validate quality on your own workload.

Generated outputs may be inaccurate or unsuitable for a given use case. Users are responsible for testing behavior, applying appropriate safeguards, and complying with applicable licenses and laws.

CPU-friendly GGUF builds of MagiSeek V1.1, the step-800 merged continuation of MagiSeek-Pro-V1.

These files are made from the same verified merged checkpoint. They are provided for people who want to run the model locally with llama.cpp and compatible applications, without requiring a GPU. Lower-bit files use less memory and run more easily on ordinary machines; higher-bit files preserve more of the original bfloat16 model's detail.

Files

File Quantization Practical use
MagiSeek-V1.1-Q8_0.gguf Q8_0 Highest fidelity, largest memory footprint
MagiSeek-V1.1-Q6_K.gguf Q6_K Strong quality/size balance
MagiSeek-V1.1-Q5_K_M.gguf Q5_K_M Balanced everyday local use
MagiSeek-V1.1-Q4_K_M.gguf Q4_K_M Smallest of this release set

llama.cpp example

llama-cli -m MagiSeek-V1.1-Q5_K_M.gguf \
  -c 8192 -ngl 0 \
  -p "Explain what you can help me build."

-ngl 0 is an explicit CPU-only example. Remove or increase it when using a compatible GPU. Tool execution and generated code must be reviewed and sandboxed before use.

Honest status

This is an early checkpoint, not the completed 10-epoch run. It was captured at global step 800 (approximately 0.187 epoch) and has not been benchmark-certified against the base model. See the full model card for training details, limitations, and intended use.