dragon-yi-answer-tool
is a quantized version of DRAGON Yi 6B, with 4_K_M GGUF quantization, providing a fast, small inference implementation for use on CPUs.
dragon-yi-6b
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/dragon-yi-answer-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
model = ModelCatalog().load_model("dragon-yi-answer-tool")
response = model.inference(query, add_context=text_sample)
Note: please review
config.json
in the repository for prompt wrapping information, details on the model, and full test set.
dragon-yi-answer-tool huggingface.co is an AI model on huggingface.co that provides dragon-yi-answer-tool's model effect (), which can be used instantly with this llmware dragon-yi-answer-tool model. huggingface.co supports a free trial of the dragon-yi-answer-tool model, and also provides paid use of the dragon-yi-answer-tool. Support call dragon-yi-answer-tool model through api, including Node.js, Python, http.
dragon-yi-answer-tool huggingface.co is an online trial and call api platform, which integrates dragon-yi-answer-tool's modeling effects, including api services, and provides a free online trial of dragon-yi-answer-tool, you can try dragon-yi-answer-tool online for free by clicking the link below.
llmware dragon-yi-answer-tool online free url in huggingface.co:
dragon-yi-answer-tool is an open source model from GitHub that offers a free installation service, and any user can find dragon-yi-answer-tool on GitHub to install. At the same time, huggingface.co provides the effect of dragon-yi-answer-tool install, users can directly use dragon-yi-answer-tool installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
dragon-yi-answer-tool install url in huggingface.co: