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Duplicate from mlc-ai/gemma-2-2b-it-q4f32_1-MLC

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Co-authored-by: Charlie Ruan <CharlieFRuan@users.noreply.huggingface.co>

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  1. .gitattributes +36 -0
  2. README.md +57 -0
  3. mlc-chat-config.json +86 -0
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README.md ADDED
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+ ---
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+ library_name: mlc-llm
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+ base_model: google/gemma-2-2b-it
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+ tags:
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+ - mlc-llm
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+ - web-llm
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+ ---
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+
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+ # gemma-2-2b-it-q4f32_1-MLC
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+
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+ This is the [gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) model in MLC format `q4f32_1`.
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+ The model can be used for projects [MLC-LLM](https://github.com/mlc-ai/mlc-llm) and [WebLLM](https://github.com/mlc-ai/web-llm).
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+
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+ ## Example Usage
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+
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+ Here are some examples of using this model in MLC LLM.
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+ Before running the examples, please install MLC LLM by following the [installation documentation](https://llm.mlc.ai/docs/install/mlc_llm.html#install-mlc-packages).
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+
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+ ### Chat
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+
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+ In command line, run
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+ ```bash
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+ mlc_llm chat HF://mlc-ai/gemma-2-2b-it-q4f32_1-MLC
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+ ```
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+
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+ ### REST Server
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+
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+ In command line, run
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+ ```bash
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+ mlc_llm serve HF://mlc-ai/gemma-2-2b-it-q4f32_1-MLC
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+ ```
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+
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+ ### Python API
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+
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+ ```python
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+ from mlc_llm import MLCEngine
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+
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+ # Create engine
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+ model = "HF://mlc-ai/gemma-2-2b-it-q4f32_1-MLC"
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+ engine = MLCEngine(model)
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+
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+ # Run chat completion in OpenAI API.
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+ for response in engine.chat.completions.create(
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+ messages=[{"role": "user", "content": "What is the meaning of life?"}],
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+ model=model,
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+ stream=True,
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+ ):
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+ for choice in response.choices:
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+ print(choice.delta.content, end="", flush=True)
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+ print("\n")
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+
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+ engine.terminate()
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+ ```
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+
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+ ## Documentation
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+
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+ For more information on MLC LLM project, please visit our [documentation](https://llm.mlc.ai/docs/) and [GitHub repo](http://github.com/mlc-ai/mlc-llm).
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+ {
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+ "version": "0.1.0",
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+ "model_type": "gemma2",
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+ "quantization": "q4f32_1",
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+ "model_config": {
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+ "hidden_size": 2304,
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+ "intermediate_size": 9216,
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+ "attention_bias": false,
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+ "num_attention_heads": 8,
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+ "num_key_value_heads": 4,
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+ "head_dim": 256,
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+ "num_hidden_layers": 26,
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+ "rms_norm_eps": 1e-06,
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+ "vocab_size": 256000,
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+ "hidden_activation": "gelu_pytorch_tanh",
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+ "position_embedding_base": 10000.0,
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+ "context_window_size": 4096,
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+ "prefill_chunk_size": 2048,
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+ "tensor_parallel_shards": 1,
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+ "max_batch_size": 80,
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+ "attn_logit_softcapping": 50.0,
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+ "final_logit_softcapping": 30.0,
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+ "query_pre_attn_scalar": 256,
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+ "sliding_window": 4096
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+ },
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+ "vocab_size": 256000,
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+ "context_window_size": 4096,
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+ "sliding_window_size": -1,
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+ "prefill_chunk_size": 2048,
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+ "attention_sink_size": -1,
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+ "tensor_parallel_shards": 1,
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+ "temperature": 1.0,
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+ "presence_penalty": 0.0,
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+ "frequency_penalty": 0.0,
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+ "repetition_penalty": 1.0,
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+ "top_p": 1.0,
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+ "tokenizer_files": [
38
+ "tokenizer.model",
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+ "tokenizer.json",
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+ "tokenizer_config.json"
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+ ],
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+ "tokenizer_info": {
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+ "token_postproc_method": "byte_fallback",
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+ "prepend_space_in_encode": false,
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+ "strip_space_in_decode": false
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+ },
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+ "conv_template": {
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+ "name": "gemma_instruction",
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+ "system_template": "<bos>{system_message}",
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+ "system_message": "",
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+ "system_prefix_token_ids": [
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+ 2
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+ ],
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+ "add_role_after_system_message": true,
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+ "roles": {
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+ "user": "<start_of_turn>user",
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+ "assistant": "<start_of_turn>model"
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+ },
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+ "role_templates": {
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+ "user": "{user_message}",
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+ "assistant": "{assistant_message}",
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+ "tool": "{tool_message}"
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+ },
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+ "messages": [],
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+ "seps": [
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+ "<end_of_turn>\n"
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+ ],
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+ "role_content_sep": "\n",
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+ "role_empty_sep": "\n",
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+ "stop_str": [
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+ "<end_of_turn>"
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+ ],
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+ "stop_token_ids": [
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+ 1,
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+ 107
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+ ],
77
+ "function_string": "",
78
+ "use_function_calling": false
79
+ },
80
+ "pad_token_id": 0,
81
+ "bos_token_id": 2,
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+ "eos_token_id": [
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+ 1,
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+ 107
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+ ]
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+ }
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