bling-stablelm-3b-gguf
is a quantized version of BLING Stable-LM 3B, with 4_K_M GGUF quantization, providing a fast, small inference implementation for use on CPUs.
bling-stablelm-3b
is a fact-based question-answering model, optimized for complex business documents.
To pull the model via API:
from huggingface_hub import snapshot_download
snapshot_download("llmware/bling-stablelm-3b-gguf", 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
model = ModelCatalog().load_model("llmware/bling-stablelm-3b-gguf")
response = model.inference(query, add_context=text_sample, add_prompt_engineering="default_with_context")
Note: please review
config.json
in the repository for prompt wrapping information, details on the model, and full test set.
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llmware bling-stablelm-3b-gguf online free url in huggingface.co:
bling-stablelm-3b-gguf is an open source model from GitHub that offers a free installation service, and any user can find bling-stablelm-3b-gguf on GitHub to install. At the same time, huggingface.co provides the effect of bling-stablelm-3b-gguf install, users can directly use bling-stablelm-3b-gguf installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
bling-stablelm-3b-gguf install url in huggingface.co: