Skip to main content

llama-index llms mistral-rs integration

Project description

LlamaIndex Llms Integration: mistral.rs

To use this integration, please install the Python mistralrs package:

Installation of mistralrs from PyPi

  1. Install Rust: https://rustup.rs/

    curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
    source $HOME/.cargo/env
    
  2. mistralrs depends on the openssl library.

To install it on Ubuntu:

sudo apt install libssl-dev
sudo apt install pkg-config
  1. Install it!
  • CUDA

    pip install mistralrs-cuda

  • Metal

    pip install mistralrs-metal

  • Apple Accelerate

    pip install mistralrs-accelerate

  • Intel MKL

    pip install mistralrs-mkl

  • Without accelerators

    pip install mistralrs

All installations will install the mistralrs package. The suffix on the package installed by pip only controls the feature activation.

Installation from source

Please follow the instructions here.

Usage

from llama_index.llms.mistral_rs import MistralRS
from mistralrs import Which

llm = MistralRS(
    which=Which.GGUF(
        tok_model_id="mistralai/Mistral-7B-Instruct-v0.1",
        quantized_model_id="TheBloke/Mistral-7B-Instruct-v0.1-GGUF",
        quantized_filename="mistral-7b-instruct-v0.1.Q4_K_M.gguf",
        tokenizer_json=None,
        repeat_last_n=64,
    ),
    max_new_tokens=4096,
    context_window=1024 * 5,
)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llama_index_llms_mistral_rs-0.4.0.tar.gz (6.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

llama_index_llms_mistral_rs-0.4.0-py3-none-any.whl (5.9 kB view details)

Uploaded Python 3

File details

Details for the file llama_index_llms_mistral_rs-0.4.0.tar.gz.

File metadata

File hashes

Hashes for llama_index_llms_mistral_rs-0.4.0.tar.gz
Algorithm Hash digest
SHA256 013d36cde292c3ef8590da93b68072aee8cbfb399ca8c5a7a3016b529124530c
MD5 c2271a1b37efab30b30051a4819fbe43
BLAKE2b-256 930166d26eb502551db82490507067154f8c3ccd0667b39eee4db1310f6e024e

See more details on using hashes here.

File details

Details for the file llama_index_llms_mistral_rs-0.4.0-py3-none-any.whl.

File metadata

File hashes

Hashes for llama_index_llms_mistral_rs-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 904ea03a0980c80da018f55645a9d3d45e3cbc47982b580cad3b265a6a4c7a0c
MD5 9116fcccb91b9665a2f002dc3c2ae8cd
BLAKE2b-256 47620f628f5f3b3ffe5c32c7ee9f757e6ad8f275ceb2c09a743e42183cfc2655

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page