Text Generation
PEFT
Safetensors
English
minicpm
minicpm5
minicpm5-1b
tool-calling
function-calling
tool-use
agentic
agentic-ai
ai-agent
xml-tool-calling
json-function-calling
lora
qlora
grpo
reinforcement-learning
rlhf
unsloth
trl
openbmb
conversational
small-language-model
slm
edge-ai
on-device
local-llm
efficient-llm
Eval Results (legacy)
Instructions to use ewin-reg/MiniCPM5-1B-Agentic-Tooluse-QLoRA-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ewin-reg/MiniCPM5-1B-Agentic-Tooluse-QLoRA-v3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM5-1B") model = PeftModel.from_pretrained(base_model, "ewin-reg/MiniCPM5-1B-Agentic-Tooluse-QLoRA-v3") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
- Xet hash:
- 34d201fef41cda2fe17074138c9d9d42ab27dfa32078a8cf6bde3e350517bf2c
- Size of remote file:
- 89.7 MB
- SHA256:
- 4214259885d7d88d2c4d3b34d979e8ee9941c8d492ce68572ddbe26bea1683cb
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