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- README.md +80 -0
- config.json +30 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8-opt-0-hybrid-ratio-0.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8-opt-0-hybrid-ratio-0.5.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8-opt-0-hybrid-ratio-1.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8-opt-1-hybrid-ratio-0.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8-opt-1-hybrid-ratio-0.5.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8-opt-1-hybrid-ratio-1.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g128-opt-0-hybrid-ratio-0.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g128-opt-0-hybrid-ratio-0.5.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g128-opt-0-hybrid-ratio-1.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g128-opt-1-hybrid-ratio-0.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g128-opt-1-hybrid-ratio-0.5.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g128-opt-1-hybrid-ratio-1.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g256-opt-0-hybrid-ratio-0.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g256-opt-0-hybrid-ratio-0.5.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g256-opt-0-hybrid-ratio-1.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g256-opt-1-hybrid-ratio-0.0.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g256-opt-1-hybrid-ratio-0.5.rkllm +3 -0
- deepseek-coder-6.7b-instruct-rk3588-w8a8_g256-opt-1-hybrid-ratio-1.0.rkllm +3 -0
- generation_config.json +6 -0
- model.safetensors.index.json +298 -0
- pytorch_model.bin.index.json +298 -0
- tokenizer.json +0 -0
- tokenizer_config.json +35 -0
.gitattributes
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README.md
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---
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license: other
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license_name: deepseek
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license_link: LICENSE
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---
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# deepseek-coder-6.7b-instruct-RK3588-1.1.1
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This version of deepseek-coder-6.7b-instruct has been converted to run on the RK3588 NPU using {'w8a8_g256', 'w8a8_g128', 'w8a8'} quantization.
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This model has been optimized with the following LoRA:
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Compatible with RKLLM version: 1.1.1
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###Useful links:
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[Official RKLLM GitHub](https://github.com/airockchip/rknn-llm)
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[RockhipNPU Reddit](https://reddit.com/r/RockchipNPU)
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[EZRKNN-LLM](https://github.com/Pelochus/ezrknn-llm/)
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Pretty much anything by these folks: [marty1885][https://github.com/marty1885] and [happyme531](https://huggingface.co/happyme531)
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# Original Model Card for base model, deepseek-coder-6.7b-instruct, below:
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<p align="center">
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<img width="1000px" alt="DeepSeek Coder" src="https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/pictures/logo.png?raw=true">
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</p>
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<p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://coder.deepseek.com/">[🤖 Chat with DeepSeek Coder]</a> | <a href="https://discord.gg/Tc7c45Zzu5">[Discord]</a> | <a href="https://github.com/guoday/assert/blob/main/QR.png?raw=true">[Wechat(微信)]</a> </p>
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<hr>
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### 1. Introduction of Deepseek Coder
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Deepseek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code corpus by employing a window size of 16K and a extra fill-in-the-blank task, to support project-level code completion and infilling. For coding capabilities, Deepseek Coder achieves state-of-the-art performance among open-source code models on multiple programming languages and various benchmarks.
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- **Massive Training Data**: Trained from scratch fon 2T tokens, including 87% code and 13% linguistic data in both English and Chinese languages.
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- **Highly Flexible & Scalable**: Offered in model sizes of 1.3B, 5.7B, 6.7B, and 33B, enabling users to choose the setup most suitable for their requirements.
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- **Superior Model Performance**: State-of-the-art performance among publicly available code models on HumanEval, MultiPL-E, MBPP, DS-1000, and APPS benchmarks.
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- **Advanced Code Completion Capabilities**: A window size of 16K and a fill-in-the-blank task, supporting project-level code completion and infilling tasks.
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### 2. Model Summary
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deepseek-coder-6.7b-instruct is a 6.7B parameter model initialized from deepseek-coder-6.7b-base and fine-tuned on 2B tokens of instruction data.
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- **Home Page:** [DeepSeek](https://deepseek.com/)
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- **Repository:** [deepseek-ai/deepseek-coder](https://github.com/deepseek-ai/deepseek-coder)
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- **Chat With DeepSeek Coder:** [DeepSeek-Coder](https://coder.deepseek.com/)
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### 3. How to Use
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Here give some examples of how to use our model.
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#### Chat Model Inference
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct", trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
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messages=[
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{ 'role': 'user', 'content': "write a quick sort algorithm in python."}
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]
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inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
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# tokenizer.eos_token_id is the id of <|EOT|> token
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outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, top_k=50, top_p=0.95, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
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print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True))
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```
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### 4. License
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This code repository is licensed under the MIT License. The use of DeepSeek Coder models is subject to the Model License. DeepSeek Coder supports commercial use.
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See the [LICENSE-MODEL](https://github.com/deepseek-ai/deepseek-coder/blob/main/LICENSE-MODEL) for more details.
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### 5. Contact
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If you have any questions, please raise an issue or contact us at [[email protected]](mailto:[email protected]).
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config.json
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{
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"_name_or_path": "/3fs-jd/prod/deepseek/shared/zhuqihao/public_model/deepseek-coder-7b-instruct2",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"bos_token_id": 32013,
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"eos_token_id": 32021,
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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": 11008,
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"max_position_embeddings": 16384,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 32,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
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"rope_scaling": {
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"factor": 4.0,
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"type": "linear"
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},
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"rope_theta": 100000,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.34.1",
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"use_cache": true,
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"vocab_size": 32256
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}
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|
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}
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tokenizer.json
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tokenizer_config.json
ADDED
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{
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"add_bos_token": true,
|
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+
"add_eos_token": false,
|
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+
"bos_token": {
|
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+
"__type": "AddedToken",
|
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+
"content": "<|begin▁of▁sentence|>",
|
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+
"lstrip": false,
|
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+
"normalized": true,
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+
"rstrip": false,
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"single_word": false
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+
},
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"clean_up_tokenization_spaces": false,
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|EOT|>",
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"lstrip": false,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"legacy": true,
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"model_max_length": 16384,
|
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"pad_token": {
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"__type": "AddedToken",
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"content": "<|end▁of▁sentence|>",
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"sp_model_kwargs": {},
|
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+
"unk_token": null,
|
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+
"tokenizer_class": "LlamaTokenizerFast",
|
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+
"chat_template": "{% if not add_generation_prompt is defined %}\n{% set add_generation_prompt = false %}\n{% endif %}\n{%- set ns = namespace(found=false) -%}\n{%- for message in messages -%}\n {%- if message['role'] == 'system' -%}\n {%- set ns.found = true -%}\n {%- endif -%}\n{%- endfor -%}\n{{bos_token}}{%- if not ns.found -%}\n{{'You are an AI programming assistant, utilizing the Deepseek Coder model, developed by Deepseek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer\\n'}}\n{%- endif %}\n{%- for message in messages %}\n {%- if message['role'] == 'system' %}\n{{ message['content'] }}\n {%- else %}\n {%- if message['role'] == 'user' %}\n{{'### Instruction:\\n' + message['content'] + '\\n'}}\n {%- else %}\n{{'### Response:\\n' + message['content'] + '\\n<|EOT|>\\n'}}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{% if add_generation_prompt %}\n{{'### Response:'}}\n{% endif %}"
|
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+
}
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