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Model: defog/sqlcoder-34b-alpha Source: Original Platform
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---
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license: cc-by-4.0
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language:
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- en
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pipeline_tag: text-generation
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---
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# Defog SQLCoder
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**Updated on Nov 14 to reflect benchmarks for SQLCoder-34B**
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Defog's SQLCoder is a state-of-the-art LLM for converting natural language questions to SQL queries.
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[Interactive Demo](https://defog.ai/sqlcoder-demo/) | [🤗 HF Repo](https://huggingface.co/defog/sqlcoder-34b-alpha) | [♾️ Colab](https://colab.research.google.com/drive/1z4rmOEiFkxkMiecAWeTUlPl0OmKgfEu7?usp=sharing) | [🐦 Twitter](https://twitter.com/defogdata)
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## TL;DR
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SQLCoder-34B is a 34B parameter model that outperforms `gpt-4` and `gpt-4-turbo` for natural language to SQL generation tasks on our [sql-eval](https://github.com/defog-ai/sql-eval) framework, and significantly outperforms all popular open-source models.
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SQLCoder-34B is fine-tuned on a base CodeLlama model.
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## Results on novel datasets not seen in training
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| model | perc_correct |
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|-|-|
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| defog-sqlcoder-34b | 84.0 |
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| gpt4-turbo-2023-11-09 | 82.5 |
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| gpt4-2023-11-09 | 82.5 |
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| defog-sqlcoder2 | 77.5 |
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| gpt4-2023-08-28 | 74.0 |
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| defog-sqlcoder-7b | 71.0 |
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| gpt-3.5-2023-10-04 | 66.0 |
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| claude-2 | 64.5 |
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| gpt-3.5-2023-08-28 | 61.0 |
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| claude_instant_1 | 61.0 |
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| text-davinci-003 | 52.5 |
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## License
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The code in this repo (what little there is of it) is Apache-2 licensed. The model weights have a `CC BY-SA 4.0` license. The TL;DR is that you can use and modify the model for any purpose – including commercial use. However, if you modify the weights (for example, by fine-tuning), you must open-source your modified weights under the same license terms.
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## Training
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Defog was trained on more than 20,000 human-curated questions. These questions were based on 10 different schemas. None of the schemas in the training data were included in our evaluation framework.
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You can read more about our [training approach](https://defog.ai/blog/open-sourcing-sqlcoder2-7b/) and [evaluation framework](https://defog.ai/blog/open-sourcing-sqleval/).
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## Results by question category
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We classified each generated question into one of 5 categories. The table displays the percentage of questions answered correctly by each model, broken down by category.
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| | date | group_by | order_by | ratio | join | where |
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| -------------- | ---- | -------- | -------- | ----- | ---- | ----- |
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| sqlcoder-34b | 80 | 94.3 | 88.6 | 74.3 | 82.9 | 82.9 |
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| gpt-4 | 68 | 94.3 | 85.7 | 77.1 | 85.7 | 80 |
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| sqlcoder2-15b | 76 | 80 | 77.1 | 60 | 77.1 | 77.1 |
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| sqlcoder-7b | 64 | 82.9 | 74.3 | 54.3 | 74.3 | 74.3 |
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| gpt-3.5 | 68 | 77.1 | 68.6 | 37.1 | 71.4 | 74.3 |
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| claude-2 | 52 | 71.4 | 74.3 | 57.1 | 65.7 | 62.9 |
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| claude-instant | 48 | 71.4 | 74.3 | 45.7 | 62.9 | 60 |
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| gpt-3 | 32 | 71.4 | 68.6 | 25.7 | 57.1 | 54.3 |
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<img width="831" alt="image" src="https://github.com/defog-ai/sqlcoder/assets/5008293/79c5bdc8-373c-4abd-822e-e2c2569ed353">
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## Using SQLCoder
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You can use SQLCoder via the `transformers` library by downloading our model weights from the Hugging Face repo. We have added sample code for [inference](./inference.py) on a [sample database schema](./metadata.sql).
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```bash
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python inference.py -q "Question about the sample database goes here"
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# Sample question:
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# Do we get more revenue from customers in New York compared to customers in San Francisco? Give me the total revenue for each city, and the difference between the two.
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```
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You can also use a demo on our website [here](https://defog.ai/sqlcoder-demo)
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## Hardware Requirements
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SQLCoder-34B has been tested on a 4xA10 GPU with `float16` weights. You can also load an 8-bit and 4-bit quantized version of the model on consumer GPUs with 20GB or more of memory – like RTX 4090, RTX 3090, and Apple M2 Pro, M2 Max, or M2 Ultra Chips with 20GB or more of memory.
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## Todo
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- [x] Open-source the v1 model weights
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- [x] Train the model on more data, with higher data variance
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- [ ] Tune the model further with Reward Modelling and RLHF
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- [ ] Pretrain a model from scratch that specializes in SQL analysis
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}
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"model.layers.9.self_attn.q_proj.weight": "pytorch_model-00002-of-00007.bin",
|
||||
"model.layers.9.self_attn.v_proj.weight": "pytorch_model-00002-of-00007.bin",
|
||||
"model.norm.weight": "pytorch_model-00007-of-00007.bin"
|
||||
}
|
||||
}
|
||||
33
special_tokens_map.json
Normal file
33
special_tokens_map.json
Normal file
@@ -0,0 +1,33 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"▁<PRE>",
|
||||
"▁<MID>",
|
||||
"▁<SUF>",
|
||||
"▁<EOT>",
|
||||
"▁<PRE>",
|
||||
"▁<MID>",
|
||||
"▁<SUF>",
|
||||
"▁<EOT>"
|
||||
],
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:1d0fad9b4268298c57c3510c076611229453b3145fe244aa84e52b102df4f152
|
||||
size 1843492
|
||||
85
tokenizer_config.json
Normal file
85
tokenizer_config.json
Normal file
@@ -0,0 +1,85 @@
|
||||
{
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32000": {
|
||||
"content": "▁<PRE>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32001": {
|
||||
"content": "▁<MID>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32002": {
|
||||
"content": "▁<SUF>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"32003": {
|
||||
"content": "▁<EOT>",
|
||||
"lstrip": true,
|
||||
"normalized": false,
|
||||
"rstrip": true,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"▁<PRE>",
|
||||
"▁<MID>",
|
||||
"▁<SUF>",
|
||||
"▁<EOT>",
|
||||
"▁<PRE>",
|
||||
"▁<MID>",
|
||||
"▁<SUF>",
|
||||
"▁<EOT>"
|
||||
],
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"eot_token": "▁<EOT>",
|
||||
"fill_token": "<FILL_ME>",
|
||||
"legacy": null,
|
||||
"middle_token": "▁<MID>",
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"prefix_token": "▁<PRE>",
|
||||
"sp_model_kwargs": {},
|
||||
"suffix_token": "▁<SUF>",
|
||||
"tokenizer_class": "CodeLlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user