| | --- |
| | license: apache-2.0 |
| | --- |
| | |
| | # SLIM-RATINGS |
| |
|
| | <!-- Provide a quick summary of what the model is/does. --> |
| |
|
| |
|
| | **slim-ratings-tool** is a 4_K_M quantized GGUF version of slim-sentiment, providing a small, fast inference implementation, optimized for multi-model concurrent deployment. |
| |
|
| | [**slim-ratings**](https://huggingface.co/llmware/slim-ratings) is part of the SLIM ("**S**tructured **L**anguage **I**nstruction **M**odel") series, providing a set of small, specialized decoder-based LLMs, fine-tuned for function-calling. |
| |
|
| | To pull the model via API: |
| |
|
| | from huggingface_hub import snapshot_download |
| | snapshot_download("llmware/slim-ratings-tool", local_dir="/path/on/your/machine/", local_dir_use_symlinks=False) |
| | |
| | |
| | Load in your favorite GGUF inference engine, or try with llmware as follows: |
| |
|
| | from llmware.models import ModelCatalog |
| | |
| | # to load the model and make a basic inference |
| | model = ModelCatalog().load_model("slim-ratings-tool") |
| | response = model.function_call(text_sample) |
| | |
| | # this one line will download the model and run a series of tests |
| | ModelCatalog().tool_test_run("slim-ratings-tool", verbose=True) |
| | |
| |
|
| | Slim models can also be loaded even more simply as part of a multi-model, multi-step LLMfx calls: |
| |
|
| | from llmware.agents import LLMfx |
| | |
| | llm_fx = LLMfx() |
| | llm_fx.load_tool("ratings") |
| | response = llm_fx.ratings(text) |
| | |
| |
|
| | Note: please review [**config.json**](https://huggingface.co/llmware/slim-ratings-tool/blob/main/config.json) in the repository for prompt wrapping information, details on the model, and full test set. |
| |
|
| |
|
| | ## Model Card Contact |
| |
|
| | Darren Oberst & llmware team |
| |
|
| | [Any questions? Join us on Discord](https://discord.gg/MhZn5Nc39h) |
| |
|
