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Browse files- README.md +68 -0
- config.json +41 -0
- generation_config.json +7 -0
- model-00001-of-00003.safetensors +3 -0
- model-00002-of-00003.safetensors +3 -0
- model-00003-of-00003.safetensors +3 -0
- model.safetensors.index.json +554 -0
- pytorch_model.bin.index.json +554 -0
- special_tokens_map.json +38 -0
- tokenizer.model +3 -0
- tokenizer_config.json +98 -0
README.md
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---
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license: apache-2.0
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pipeline_tag: text-generation
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---
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<div align="center">
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<img src="https://raw.githubusercontent.com/InternLM/lmdeploy/0be9e7ab6fe9a066cfb0a09d0e0c8d2e28435e58/resources/lmdeploy-logo.svg" width="450"/>
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</div>
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# INT4 Weight-only Quantization and Deployment (W4A16)
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LMDeploy adopts [AWQ](https://arxiv.org/abs/2306.00978) algorithm for 4bit weight-only quantization. By developed the high-performance cuda kernel, the 4bit quantized model inference achieves up to 2.4x faster than FP16.
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LMDeploy supports the following NVIDIA GPU for W4A16 inference:
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- Turing(sm75): 20 series, T4
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- Ampere(sm80,sm86): 30 series, A10, A16, A30, A100
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- Ada Lovelace(sm90): 40 series
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Before proceeding with the quantization and inference, please ensure that lmdeploy is installed.
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```shell
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pip install lmdeploy[all]
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```
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This article comprises the following sections:
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<!-- toc -->
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- [Inference](#inference)
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- [Evaluation](#evaluation)
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- [Service](#service)
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<!-- tocstop -->
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## Inference
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Trying the following codes, you can perform the batched offline inference with the quantized model:
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```python
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from lmdeploy import pipeline, TurbomindEngineConfig
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engine_config = TurbomindEngineConfig(model_format='awq')
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pipe = pipeline("internlm/internlm2_5-7b-chat-4bit", backend_config=engine_config)
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response = pipe(["Hi, pls intro yourself", "Shanghai is"])
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print(response)
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```
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For more information about the pipeline parameters, please refer to [here](https://github.com/InternLM/lmdeploy/blob/main/docs/en/inference/pipeline.md).
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## Evaluation
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Please overview [this guide](https://opencompass.readthedocs.io/en/latest/advanced_guides/evaluation_turbomind.html) about model evaluation with LMDeploy.
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## Service
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LMDeploy's `api_server` enables models to be easily packed into services with a single command. The provided RESTful APIs are compatible with OpenAI's interfaces. Below are an example of service startup:
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```shell
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lmdeploy serve api_server internlm/internlm2_5-7b-chat-4bit --backend turbomind --model-format awq
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```
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The default port of `api_server` is `23333`. After the server is launched, you can communicate with server on terminal through `api_client`:
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```shell
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lmdeploy serve api_client http://0.0.0.0:23333
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```
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You can overview and try out `api_server` APIs online by swagger UI at `http://0.0.0.0:23333`, or you can also read the API specification from [here](https://github.com/InternLM/lmdeploy/blob/main/docs/en/serving/restful_api.md).
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config.json
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{
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"_name_or_path": "/nvme/shared_data/InternLM/internlm2_5-7b-chat",
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"architectures": [
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"InternLM2ForCausalLM"
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],
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"attn_implementation": "eager",
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"auto_map": {
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"AutoConfig": "configuration_internlm2.InternLM2Config",
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"AutoModel": "modeling_internlm2.InternLM2ForCausalLM",
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"AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM"
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},
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"bias": false,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"fp16": true,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "internlm2",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pad_token_id": 2,
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"quantization_config": {
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"bits": 4,
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"group_size": 128,
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"quant_method": "awq",
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"version": "gemm",
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"zero_point": true
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},
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 1000000,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.40.1",
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"use_cache": false,
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"vocab_size": 92544
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 2,
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"transformers_version": "4.40.1"
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}
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model-00001-of-00003.safetensors
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size 1384550088
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model-00002-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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model-00003-of-00003.safetensors
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version https://git-lfs.github.com/spec/v1
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model.safetensors.index.json
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special_tokens_map.json
ADDED
@@ -0,0 +1,38 @@
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|
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|
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|
1 |
+
{
|
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+
"additional_special_tokens": [
|
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+
"<|im_start|>",
|
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+
"<|im_end|>",
|
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"<|action_start|>",
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"<|action_end|>",
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"<|interpreter|>",
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"<|plugin|>"
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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}
|
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tokenizer.model
ADDED
@@ -0,0 +1,3 @@
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|
1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:f868398fc4e05ee1e8aeba95ddf18ddcc45b8bce55d5093bead5bbf80429b48b
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size 1477754
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tokenizer_config.json
ADDED
@@ -0,0 +1,98 @@
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3 |
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|
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|
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|
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|
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},
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|
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|
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|
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|
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|
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|
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|
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null
|
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]
|
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"unk_token": "<unk>"
|
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