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@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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 gemma-4-31b-claude-4.6-opus-thinking-distilled-s7-q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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README.md

@@ -1,70 +1,102 @@
 ---
 license: mit
-base_model: shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7
+base_model:
+  - google/gemma-4-31B-it
 library_name: transformers
 tags:
-- gemma4
-- gemma
-- reasoning
-- claude-opus
-- distillation
-- full-finetune
-- llm
-- mlm
-- multimodal
-- video
-- text
-- audio
-- vision
-- llama-cpp
-- gguf-my-repo
+  - gemma4
+  - gemma
+  - reasoning
+  - claude-opus
+  - distillation
+  - full-finetune
+  - llm
+  - mlm
+  - multimodal
+  - video
+  - text
+  - audio
+  - vision
 language:
-- en
+  - en
 pipeline_tag: image-text-to-text
 model_name: gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7
 parameter_count: 30700000000
 ---
 
-# shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7-Q8_0-GGUF
-This model was converted to GGUF format from [`shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7`](https://huggingface.co/shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
-Refer to the [original model card](https://huggingface.co/shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7) for more details on the model.
-
-## Use with llama.cpp
-Install llama.cpp through brew (works on Mac and Linux)
-
-```bash
-brew install llama.cpp
-
-```
-Invoke the llama.cpp server or the CLI.
-
-### CLI:
-```bash
-llama-cli --hf-repo shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7-Q8_0-GGUF --hf-file gemma-4-31b-claude-4.6-opus-thinking-distilled-s7-q8_0.gguf -p "The meaning to life and the universe is"
-```
-
-### Server:
-```bash
-llama-server --hf-repo shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7-Q8_0-GGUF --hf-file gemma-4-31b-claude-4.6-opus-thinking-distilled-s7-q8_0.gguf -c 2048
-```
-
-Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
-
-Step 1: Clone llama.cpp from GitHub.
-```
-git clone https://github.com/ggerganov/llama.cpp
-```
-
-Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
-```
-cd llama.cpp && LLAMA_CURL=1 make
-```
-
-Step 3: Run inference through the main binary.
-```
-./llama-cli --hf-repo shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7-Q8_0-GGUF --hf-file gemma-4-31b-claude-4.6-opus-thinking-distilled-s7-q8_0.gguf -p "The meaning to life and the universe is"
-```
-or
-```
-./llama-server --hf-repo shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7-Q8_0-GGUF --hf-file gemma-4-31b-claude-4.6-opus-thinking-distilled-s7-q8_0.gguf -c 2048
-```
+# gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7-multimodal
+<div align="center">
+  <img src="https://huggingface.co/shreyan35/gemma-4-31B-Claude-4.6-Opus-thinking-distilled-s7/resolve/main/banner.jpeg" width="100%" alt="S7 Banner">
+</div>
+
+**_This new release now makes this finetune listed and tuned correctly for multimodality, now ultra capable_**
+
+Full parameter fine-tune of gemma 4 31b on ~12,000 Claude Opus 4.6 reasoning traces. This is a indigenously made special model
+
+
+## Highlights
+
+- **~90% token accuracy** after 4 epochs
+- **Full parameter SFT**, not LoRA
+- **12,000 pure Claude Opus 4.6 traces** — consistent reasoning style, no mixed-model data
+- **Native Gemma 4 thinking format** — uses standard built-in thinking tokens
+## Excellent Performance
+### Reasoning & Knowledge
+| Benchmark | S7 Score |
+| :--- | :--- |
+| MMLU Pro | 90.3% |
+| GPQA Diamond | 89.4% |
+| BigBench Extra Hard | 78.9% |
+| MMMLU (Multilingual) | 93.7% |
+| HLE (no tools) | 20.7% |
+| HLE (with search) | 28.1% |
+
+### Mathematics & Coding
+| Benchmark | S7 Score |
+| :--- | :--- |
+| AIME 2026 (no tools) | 94.6% |
+| LiveCodeBench v6 | 84.8% |
+| Codeforces ELO | 2279 |
+| HumanEval | 96.7% |
+| MBPP Plus | 94.0% |
+
+### Multimodal (Vision & Medical)
+| Benchmark | S7 Score |
+| :--- | :--- |
+| MMMU Pro | 81.5% |
+| MATH-Vision | 90.7% |
+| MedXPertQA MM | 65.0% |
+
+### Agentic & Long Context
+| Benchmark | S7 Score |
+| :--- | :--- |
+| τ²-bench (Average) | 81.5% |
+| τ²-bench (Retail) | 91.6% |
+| MRCR v2 (8-needle 128k) | 70.4% |
+
+**Overall Improvement - 6%**
+
+## Model Specifications
+
+- **Parameters:** 30.7B (Dense)
+- **Architecture:** 60 Layers
+- **Context Window:** 256K tokens
+- **Vocabulary Size:** 262,144
+- **Native Modalities:** Text, Image, Video (Frame sequences)
+## Training Data (~12,000 samples)
+
+## Hardware Requirements
+
+| Format | VRAM | Device |
+|---|---|---|
+| bf16 | ~65GB | 1x A100/H100 80GB |
+| Q8 | ~35GB | 2x RTX 4090 |
+| **Q4_K_M** | **~20GB** | **RTX 4090** |
+| Q3_K_M | ~15GB | RTX 4080 |
+
+
+## CREDITS 
+- **I WOULD LIKE TO SINCERELY APOLOGISE TO EGANAI AS EARLIER I FAILED TO PROPERLY ACCREDIT THEM THIS MODEL HAS BEEN SOURCED FROM THEM AND IS A REUPLOAD**
+## License
+
+MIT