TeichAI/claude-4.5-opus-high-reasoning-250x
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How to use EclipseMist/gpt-oss-20b-Opus-4.5-distill-EXP 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 EclipseMist/gpt-oss-20b-Opus-4.5-distill-EXP 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 EclipseMist/gpt-oss-20b-Opus-4.5-distill-EXP to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for EclipseMist/gpt-oss-20b-Opus-4.5-distill-EXP to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="EclipseMist/gpt-oss-20b-Opus-4.5-distill-EXP",
max_seq_length=2048,
)This model was finetuned and converted to GGUF format using Unsloth.
This was trained on the TeichAI Opus 4.5 dataset https://huggingface.co/datasets/TeichAI/claude-4.5-opus-high-reasoning-250x
Since the dataset is 250x examples its for making a style distill there is simply not enough juicy data to create a "Mini Opus"
To do that you would likely need hundreds of thousands of examples and billions of tokens. Even then its only 20b parameters there is only so much that a small model can learn.
It still fails at tool calls in LM studio like the stock GPT OSS 20b does.