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Model: cascade-tech/Ministral-3-3B-Instruct-2512-BF16-llama-text
Source: Original Platform

README.md

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+---
+base_model: mistralai/Ministral-3-3B-Instruct-2512-BF16
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- llama
+- ministral
+- text-only
+---
+
+# Ministral-3 3B Instruct BF16 Llama Text
+
+Text-only Llama-compatible conversion of
+`mistralai/Ministral-3-3B-Instruct-2512-BF16`.
+
+What changed:
+
+- dropped vision and multimodal projector tensors
+- stripped the Mistral3 `language_model.` wrapper from text weights
+- wrote a plain `LlamaForCausalLM` config
+- kept tokenizer assets and chat template with the corrected regex
+- kept chat formatting in `chat_template.jinja`
+- removed the strict user/assistant alternation assertion from the template
+- left tokenizer loading on the generic fast backend, not `LlamaTokenizerFast`
+
+Verification:
+
+- reference: `mistralai/Ministral-3-3B-Instruct-2512-BF16`
+- candidate: this checkpoint
+- dataset: `/home/alvion/valve/services/training/datasets/think2-2025-12-07_gpt-5.4_reasoning.jsonl`
+- rows: 3
+- max length: 512
+- tokenizer IDs: identical
+- worst KL: 0
+- worst logit diff: 0
+- plain candidate `AutoTokenizer` matched the fixed reference tokenizer
+
+Conversion tools: https://github.com/cascade-tech-ai/mistral-convert