hvss/dispatch-7b-data
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How to use hvss/Dispatch-7B-LoRA with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for hvss/Dispatch-7B-LoRA to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for hvss/Dispatch-7B-LoRA to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hvss/Dispatch-7B-LoRA to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="hvss/Dispatch-7B-LoRA",
max_seq_length=2048,
)QLoRA adapter (r=16, attention + MLP projections) for Dispatch-7B, an agent orchestrator built on Mistral 7B Instruct v0.3 that routes agentic work: request + tool catalog in β JSON execution plan out. 97.4% valid-plan rate on held-out tasks β full evaluation, usage, and prompt format on the main model card.
Use this repo to:
For plain inference, prefer the merged weights or the GGUF quants.
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained(
"hvss/Dispatch-7B-LoRA", max_seq_length=3072, load_in_4bit=True,
)
License: Apache 2.0.
Base model
mistralai/Mistral-7B-v0.3