Instructions to use Osyrs/StatZ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Osyrs/StatZ with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Osyrs/StatZ", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use Osyrs/StatZ with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
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 Osyrs/StatZ to start chatting
Install Unsloth Studio (Windows)
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 Osyrs/StatZ to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Osyrs/StatZ to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Osyrs/StatZ", max_seq_length=2048, )
initial commit: create model card for statistical analysis llm
Browse filesAdd comprehensive metadata schema, Apache 2.0 license declaration, evaluation benchmarks, and strict JSON output formatting guidelines.
README.md
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---
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license: apache-2.0
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---
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license: apache-2.0
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datasets:
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- Effyis/Table-Extraction
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- artefactory/Argimi-Ardian-Finance-10k-text-image
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- dreamerdeo/finqa
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language:
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- en
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metrics:
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- f1
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- exact_match
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- cer
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- accuracy
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base_model:
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- deepseek-ai/DeepSeek-V4-Flash
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- Qwen/Qwen3.6-35B-A3B
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- google/gemma-4-31B-it
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new_version: deepseek-ai/DeepSeek-R1
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library_name: transformers
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tags:
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- finance
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- text-generation-inference
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- tabular-data
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- statistics
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- unsloth
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- trl
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- outlines
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