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Bielik-11B-v2.2-Instruct-GGUF-IQ-Imatrix

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metadata
language:
  - pl
license: apache-2.0
library_name: transformers
tags:
  - finetuned
  - gguf
inference: false
pipeline_tag: text-generation
base_model: speakleash/Bielik-11B-v2.2-Instruct

Bielik-11B-v2.2-Instruct-GGUF-IQ-Imatrix

This is an experimental version of the repository containing quantized Bielik-11B-v.2.2-Instruct models using calibration with importance matrix (imatrix). Models with low precision (2bit, 3bit) for use in mobile devices or minicomputers. Note that these models should be used mainly in instructional mode (not chat). We recommend setting low temperature values. Models with higher precision 4-8bit after calibration may show better quality than models without calibration.

DISCLAIMER: Be aware that quantised models show reduced response quality and possible hallucinations!

Available quantization formats:

  • IQ1_M: (1.75bit) Extremely low quality, not recommended.
  • IQ2_XXS: Lower quality, uses SOTA techniques to be usable.
  • IQ3_XXS: Lower quality, new method with decent performance, comparable to Q3 quants.
  • IQ4_XS: Decent quality, smaller than Q4_K_S with similar performance, recommended.
  • Q4_K_M: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K
  • Q5_K_M: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K
  • Q6_K: Uses Q8_K for all tensors
  • Q8_0: Almost indistinguishable from float16. High resource use and slow. Not recommended for most users.

Ollama Modfile

The GGUF file can be used with Ollama. To do this, you need to import the model using the configuration defined in the Modfile. For model eg. Bielik-11B-v2.2-Instruct.Q4_K_M.gguf (full path to model location) Modfile looks like:

FROM ./Bielik-11B-v2.2-Instruct.Q4_K_M.gguf

TEMPLATE """<s>{{ if .System }}<|start_header_id|>system<|end_header_id|>

{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>

{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>

{{ .Response }}<|eot_id|>"""

PARAMETER stop "<|start_header_id|>"
PARAMETER stop "<|end_header_id|>"
PARAMETER stop "<|eot_id|>"

# Remeber to set low temperature for experimental models (1-3bits)
PARAMETER temperature 0.1

Model description:

About GGUF

GGUF is a new format introduced by the llama.cpp team on August 21st 2023.

Here is an incomplete list of clients and libraries that are known to support GGUF:

  • llama.cpp. The source project for GGUF. Offers a CLI and a server option.
  • text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
  • KoboldCpp, a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
  • GPT4All, a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
  • LM Studio, an easy-to-use and powerful local GUI for Windows, macOS (Silicon) and Linux, with GPU acceleration
  • LoLLMS Web UI, a great web UI with many interesting and unique features, including a full model library for easy model selection.
  • Faraday.dev, an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
  • llama-cpp-python, a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
  • candle, a Rust ML framework with a focus on performance, including GPU support, and ease of use.
  • ctransformers, a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note ctransformers has not been updated in a long time and does not support many recent models.

Responsible for model quantization

  • Remigiusz KinasSpeakLeash - team leadership, conceptualizing, calibration data preparation, process creation and quantized model delivery.

Contact Us

If you have any questions or suggestions, please use the discussion tab. If you want to contact us directly, join our Discord SpeakLeash.