base on 0️⃣1️⃣🤗 BitNet-Transformers: Huggingface Transformers Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch with Llama(2) Architecture # 0️⃣1️⃣🤗 BitNet-Transformers: Huggingface Transformers Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch with Llama(2) Architecture   - Paper Link: https://arxiv.org/pdf/2310.11453.pdf ## Prepare Dev env ```bash # Clone this repo git clone https://github.com/beomi/bitnet-transformers cd bitnet-transformers # Install requirements pip install -r clm_requirements.txt # Clone transformers repo git clone https://github.com/huggingface/transformers pip install -e transformers # Update Llama(2) model rm ./transformers/src/transformers/models/llama/modeling_llama.py ln -s $(pwd)/bitnet_llama/modeling_llama.py ./transformers/src/transformers/models/llama/modeling_llama.py ``` We'll overwrite `bitnet_llama/modeling_llama.py` into `transformers`. Since the file is linked, any changes made to the file will be reflected in the `transformers` repo. ## Train Wikitext-103  > You can track metrics via wandb ```bash ./train_wikitext.sh ``` ## GPU Mem Usage Comparison **Train Config** - Batch size: 1 - Gradient accumulation: 1 - Seq length: 2048 - Model: `LLamaForCausalLM` with `BitLinear` layer - Model size: 47,452,672 (47.5M) **Original LLAMA - 16bit** - Uses **250MB** GPU memory for Model weights **BitLLAMA - Mixed 16bit** - Uses **200MB** GPU memory for Model weights - Use bf16(or fp16) to store model weights - Use int8 to store `-1`/`1` 1-bit weights - Use more memory when training than original LLAMA: It saves 1-bit weight and 16bit weight together **BitLLAMA - 8bit** - Uses **100MB** GPU memory for Model weights - Use bf16(or fp16) on-the-fly when needed - Use 8bit to save 1-bit BitLinear weight & other weights **BitLLAMA - 1bit** - Use bf16(or fp16) on-the-fly when needed - Use 1bit to save 1-bit weight ```bash TBD ``` ## Todo - [x] Add `BitLinear` layer - [x] Add `LLamaForCausalLM` model with `BitLinear` layer - [x] Update `.save_pretrained` method (for 1-bit weight saving) - [x] Add sample code for LM training - [ ] Update `BitLinear` layer to use 1-bit weight - [ ] Use uint8 instead of bfloat16 - [ ] Use custom cuda kernel for 1-bit weight ", Assign "at most 3 tags" to the expected json: {"id":"8186","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"