Add InternLM2Tokenizer support (BPE tokenizer)#1023
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baijumeswani merged 1 commit intomicrosoft:mainfrom Feb 7, 2026
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Add InternLM2Tokenizer support (BPE tokenizer)#1023baijumeswani merged 1 commit intomicrosoft:mainfrom
baijumeswani merged 1 commit intomicrosoft:mainfrom
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InternLM2 models use the same BPE/LLaMA tokenizer format as Llama. This registers InternLM2Tokenizer so models exported with tokenizer_class: InternLM2Tokenizer in tokenizer_config.json are recognized at runtime. Ref: https://huggingface.co/internlm/internlm2-1_8b
baijumeswani
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kunal-vaishnavi
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Feb 7, 2026
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- Bump extensions commit to 087953cd (includes InternLM2Tokenizer support) - Remove local patch now that support is upstream Ref: microsoft/onnxruntime-extensions#1023
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# Add InternLM2 Model Support Adds full support for InternLM2 model family (1.8B, 7B, etc.) to ONNX Runtime GenAI. ## Changes ### Core Implementation - **New InternLM2Model builder** (`src/python/py/models/builders/internlm.py`) - Extends LlamaModel with InternLM2-specific weight mapping - GQA support: 16 query heads, 8 KV heads (2:1 ratio) - Proper grouped QKV weight splitting for GroupQueryAttention operator - **Model registration** (`builder.py`, `__init__.py`, `model_type.h`) - Maps `InternLM2ForCausalLM` → `InternLM2Model` - Adds "internlm2" to supported model types ### Tokenizer Support - **Upstream**: Contributed InternLM2Tokenizer support to [onnxruntime-extensions#1023](microsoft/onnxruntime-extensions#1023) (merged) - **Dependencies**: - Updated `cmake/deps.txt` to onnxruntime-extensions commit `087953cd` - Removed local patch in `cmake/external/onnxruntime_external_deps.cmake` - **Fix**: Set correct `model_max_length` in tokenizer_config.json (prevents 1e30 invalid values) ### Documentation - Updated README.md and src/python/py/models/README.md ## Usage Export ``` python -m onnxruntime_genai.models.builder \ --model_name internlm/internlm2-1_8b \ --output ./internlm2-cpu-int4 \ --precision int4 \ --execution_provider cpu ``` Inference ``` import onnxruntime_genai as og model = og.Model("./internlm2-cpu-int4") tokenizer = og.Tokenizer(model) ... standard generation code ``` ## Testing - ✅ InternLM2-1.8B INT4 CPU: export and inference - ✅ InternLM2-7B INT4 CPU: export tested - ✅ GQA weight splitting verified - ✅ Tokenizer recognition working ## References - Model: https://huggingface.co/internlm/internlm2-1_8b - Upstream PR: microsoft/onnxruntime-extensions#1023 --------- Signed-off-by: Rajeev Patwari <rajeevp@amd.com> Co-authored-by: Cursor <cursoragent@cursor.com>
baijumeswani
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Feb 12, 2026
# Add InternLM2 Model Support Adds full support for InternLM2 model family (1.8B, 7B, etc.) to ONNX Runtime GenAI. ## Changes ### Core Implementation - **New InternLM2Model builder** (`src/python/py/models/builders/internlm.py`) - Extends LlamaModel with InternLM2-specific weight mapping - GQA support: 16 query heads, 8 KV heads (2:1 ratio) - Proper grouped QKV weight splitting for GroupQueryAttention operator - **Model registration** (`builder.py`, `__init__.py`, `model_type.h`) - Maps `InternLM2ForCausalLM` → `InternLM2Model` - Adds "internlm2" to supported model types ### Tokenizer Support - **Upstream**: Contributed InternLM2Tokenizer support to [onnxruntime-extensions#1023](microsoft/onnxruntime-extensions#1023) (merged) - **Dependencies**: - Updated `cmake/deps.txt` to onnxruntime-extensions commit `087953cd` - Removed local patch in `cmake/external/onnxruntime_external_deps.cmake` - **Fix**: Set correct `model_max_length` in tokenizer_config.json (prevents 1e30 invalid values) ### Documentation - Updated README.md and src/python/py/models/README.md ## Usage Export ``` python -m onnxruntime_genai.models.builder \ --model_name internlm/internlm2-1_8b \ --output ./internlm2-cpu-int4 \ --precision int4 \ --execution_provider cpu ``` Inference ``` import onnxruntime_genai as og model = og.Model("./internlm2-cpu-int4") tokenizer = og.Tokenizer(model) ... standard generation code ``` ## Testing - ✅ InternLM2-1.8B INT4 CPU: export and inference - ✅ InternLM2-7B INT4 CPU: export tested - ✅ GQA weight splitting verified - ✅ Tokenizer recognition working ## References - Model: https://huggingface.co/internlm/internlm2-1_8b - Upstream PR: microsoft/onnxruntime-extensions#1023 --------- Signed-off-by: Rajeev Patwari <rajeevp@amd.com> Co-authored-by: Cursor <cursoragent@cursor.com>
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Summary
InternLM2 models use the same BPE/LLaMA tokenizer format as Llama. This registers
InternLM2Tokenizerso that models exported withtokenizer_class: InternLM2Tokenizerintokenizer_config.jsonare recognized at runtime.Changes
{"InternLM2Tokenizer", TokenType::kBPE}to the tokenizer type map inoperators/tokenizer/tokenizer_jsconfig.hppReference
Testing
Tested with InternLM2-1.8B model export and inference in onnxruntime-genai.