getllms 0.4

The LLMs Index. Download LLMs to use locally.

Illustration by Sean Sinclair on Unplash.

getllms - 0.4

The LLMs index. Uses the LMStudio Catalog.

$ pip install getllms

List All LLMs.

List all LLMs available for use. Selected for you.

import getllms

models = getllms.list_models()

Output

[
    Model(
        name='Samantha 1.1 7B',
        description='Samantha has been trained in philos…',
        files=[ …(2) ]
    ),
    Model(
        name='Redmond-Puffin-13B-V1.3',
        description='Redmond-Puffin-13B is one of the wo…',
        files=[ …(1) ]
    )
]

See Trained LLMs.

Get the trained ones for a specific model. Select the one that meets your system requirements.

models[0].files # trained samantha 1.1 7b

Output & More

Output

FileCollection(
    best=ModelFile(
        name='samantha-1.1-llama-7b.ggmlv3.q6_K.bin',
        size=5528904320,
        url='https://huggingface.co/TheBlok…'
    ),
    +1
)

---

More

Additionally, you can see all the available model files:

models[0].files.all # [ ModelFile(name='samantha-1.1-llama-…'), … ]

Download LLMs.

Download the LLM that's right for you.

best = models[0].files.best
best.download()

Output

Downloading... 116.44MB / 5.15GB (2.00%)

---

Illustration by Milad Fakurian on Unplash.

More

User guides, and many more.

Learn how to master getllms in under five minutes.

Table of Contents

TOC

1. Updating the Catalog
2. Dataclasses
   • Model
   • ModelFileCollection
     • find()
   • ModelFile
     • download()

Updating the Catalog

When getllms is downloaded, the index file is automatically installed inside of getllms.data and is already compressed.

You can get the latest version of the model catalogue using:

from getllms import download_model_data, erase_data

erase_data(reload=True) # erase the previous version
download_model_data() # download the latest ones

# now list all the models.

Dataclasses

Below is a list of attributes of the dataclasses (from getllms.model).

Model

Represents the info of an LLM model.

class Model:
    name: str
    date_published: str
    description: str
    author: dict[str, str]
    n_params: str # (e.g., 7B)
    canonical_url: str
    download_url: str # note: NOT the raw file
    trained_for: Literal['chat', 'instruct', 'other']
    files: ModelFileCollection

ModelFileCollection

A set of model files.

class ModelFileCollection:
    all: List[ModelFile]
    most_capable: ModelFile
    best: ModelFile # (alias: most_capable)
    economical: ModelFile

find()

Find a model file by name.

Args:

• name (str): The name.

def find(self, name: str) -> ModelFile

ModelFile

A model file.

class ModelFile:
    name: str
    url: str
    size: int
    quantization: str
    format: Literal['ggml', 'gguf']
    publisher: dict[str, str]

download()

Download the model.

Args:

• to (str, optional): The file destination.

def download(self, *, to: Optional[str] = None)

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