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license: apache-2.0
pipeline_tag: text-generation
library_name: transformers
base_model: unsloth/gemma-3-4b-it
GoPro.gg — fine-tuned Gemma 3 4B - Final Year Project
Merged bfloat16 coaching model for GoPro.gg (Valorant, LoL, EA FC, eFootball).
Inference Endpoints (vLLM)
Uses Transformers v4-style rope_theta / rope_scaling (not v5 rope_parameters) for vLLM 0.18 compatibility.
Tokenizer/processor metadata synced from unsloth/gemma-3-4b-it (revision 5551a22).
Tesla T4 16GB — not supported for Gemma 3 + vLLM
Gemma 3 on vLLM is stuck between two hard limits on T4:
| Option | Result on T4 |
|--------|----------------|
| --dtype bfloat16 | T4 lacks bfloat16 (compute 7.5, needs 8.0+) |
| --dtype half / float16 | vLLM rejects it: "gemma3 does not support float16 — numerical instability" |
| --dtype float32 | ~17 GB weights alone → OOM on 16 GB VRAM |
This is a known vLLM limitation, not a config bug in this repo. See vLLM forum.
Use L4 24GB, A10G 24GB, or newer (Ampere+, compute ≥ 8.0).
L4 / A10G 24GB+ (recommended)
--dtype bfloat16 --max-model-len 4096 --max-num-seqs 1 --gpu-memory-utilization 0.92 --trust-remote-code --language-model-only
T4 workarounds (if L4 unavailable)
Different GPU region on HF Inference Endpoints — try AWS/GCP regions with L4 or A10G.
GPTQ 4-bit — quantize the model (~2 GB VRAM) so T4 can serve it; AWQ is known broken for Gemma 3 (use GPTQ).
Keep Gemini/Groq as primary in
dashboards-pfe/ai-service— HF endpoint is optional until Ampere+ GPU is available.
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