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Set better defaults for free-tier users: Qwen3-1.7B model, 1024 max tokens, search disabled
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Adjust duration estimation for H200 performance - reduce conservative estimates
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Use actual parameter count for AOT decision instead of string matching
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Make AOT compilation conditional for models >= 2B parameters to optimize free tier usage
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Add AOT compilation optimization for ZeroGPU acceleration
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add 4 20b+ models after enabling dynamic gpu duration
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Add dynamic duration calculation for ZeroGPU acceleration
6073cc2
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make qwen-4b default
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disable two models that cannot run or too run too slowly on hf spaces with zerogpu
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Update app.py
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Update app.py
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Update app.py
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add original apriel 15b
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use apriel 8bit
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run Apriel on 4bit
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Add Apriel-1.5-15b-Thinker
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Update app.py
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Update app.py
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Update requirements.txt
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Update requirements.txt
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Update requirements.txt
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Update app.py
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add 4 models from qwen3 family
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add qwen3 32b awq
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Update app.py
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Update README.md
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Update requirements.txt
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Update app.py
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Update app.py
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Update app.py
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Update app.py
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Update app.py
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feat(models): add Granite-4.0-Micro and Qwen3-4B-Instruct-2507 to MODELS registry
Verified signatureAdded Granite-4.0-Micro (3B dense instruct model from IBM) under ~3B parameter category Added Qwen3-4B-Instruct-2507 (updated non-thinking instruct variant with 4B params and 256K context) under 4B–4.3B category Included detailed descriptions based on official Hugging Face model cards Maintained consistent formatting and category structurec30a7f7 -
feat(models): Added three new models
Verified signatureServiceNow-AI/Apriel-1.5-15b-Thinker (15B, multimodal reasoning) ServiceNow-AI/Apriel-5B-Instruct (5B, instruction-tuned) ai21labs/AI21-Jamba-Reasoning-3B (3B, hybrid Transformer–Mamba with 256K context) Reordered entire MODELS dictionary from largest (~15B) to smallest (~135M) Grouped models into logical size-based sections with updated descriptions using official Hugging Face metadata Enhanced model descriptions with key capabilities, benchmarks, and usage context from source model cards3c22497
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add 5 models from liquid ai
8eefe94
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add smollm2 135m multilingual
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add parser_model_ner_gemma_v0 based on gemma 3 370m it
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Add Gemma-3-270m Taiwan
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add gemma-3-270m-it
3995aec
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remove prevously added breeze models (as it didn't work), add smollm 135m taiwan
b3fd72e
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add breeze models
88f3bc6
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add 3 sub-1B TW models from ShengweiPeng
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add Qwen2.5-Taiwan-3B-Reason-GRPO & Llama-3.2-Taiwan-1B
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disable cache for better compability
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make qwen2.5-taiwan 1.5b the default
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upgrade transforemrs to 4.53.3+
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upgrade transformers to 4.46.1+
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add timm to requirements
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add access_token to model loader
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add gemma 3n, smallthinker 4b0.6b and falcon h1-1.5b
de303d7