Downloads Ā· 30 days
151
8% of all-time downloads
RichardErkhov/defog_-_sqlcoder-70b-alpha-gguf
defog_-_sqlcoder-70b-alpha-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads Ā· 30 days
151
8% of all-time downloads
All-time downloads
2K
Public
Repo size
689 GB
Likes
0
Public
Click a slice to open those files.
.gguf813 GB Ā· 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
sqlcoder-70b-alpha - GGUF
| Name | Quant method | Size |
|---|---|---|
| sqlcoder-70b-alpha.Q2_K.gguf | Q2_K | 23.71GB |
| sqlcoder-70b-alpha.Q3_K_S.gguf | Q3_K_S | 27.86GB |
| sqlcoder-70b-alpha.Q3_K.gguf | Q3_K | 30.99GB |
| sqlcoder-70b-alpha.Q3_K_M.gguf | Q3_K_M | 30.99GB |
| sqlcoder-70b-alpha.Q3_K_L.gguf | Q3_K_L | 33.67GB |
| sqlcoder-70b-alpha.IQ4_XS.gguf | IQ4_XS | 34.64GB |
| sqlcoder-70b-alpha.Q4_0.gguf | Q4_0 | 36.2GB |
| sqlcoder-70b-alpha.IQ4_NL.gguf | IQ4_NL | 36.55GB |
| sqlcoder-70b-alpha.Q4_K_S.gguf | Q4_K_S | 36.55GB |
| sqlcoder-70b-alpha.Q4_K.gguf | Q4_K | 38.58GB |
| sqlcoder-70b-alpha.Q4_K_M.gguf | Q4_K_M | 38.58GB |
| sqlcoder-70b-alpha.Q4_1.gguf | Q4_1 | 40.2GB |
| sqlcoder-70b-alpha.Q5_0.gguf | Q5_0 | 44.2GB |
| sqlcoder-70b-alpha.Q5_K_S.gguf | Q5_K_S | 44.2GB |
| sqlcoder-70b-alpha.Q5_K.gguf | Q5_K | 45.41GB |
| sqlcoder-70b-alpha.Q5_K_M.gguf | Q5_K_M | 45.41GB |
| sqlcoder-70b-alpha.Q5_1.gguf | Q5_1 | 48.2GB |
| sqlcoder-70b-alpha.Q6_K.gguf | Q6_K | 52.7GB |
| sqlcoder-70b-alpha.Q8_0.gguf | Q8_0 | 68.26GB |
A capable large language model for natural language to SQL generation. Outperforms all generalist models (including GPT-4) on text to SQL.

This is the model card of a š¤ transformers model that has been pushed on the Hub. This model card has been automatically generated.
This model is intended to be used by non-technical users to understand data inside their SQL databases. It is meant as an analytics tool, and not as a database admin tool.
This model has not been trained to reject malicious requests from users with write access to databases, and should only be used by users with read-only access.
Use the code here to get started with the model.
This model was evaluated on SQL-Eval, a PostgreSQL based evaluation framework developed by Defog for testing and alignment of model capabilities.
You can read more about the methodology behind SQLEval here.
We classified each generated question into one of 6 categories. The table displays the percentage of questions answered correctly by each model, broken down by category.
| date | group_by | order_by | ratio | join | where | |
|---|---|---|---|---|---|---|
| sqlcoder-70b | 96 | 91.4 | 97.1 | 85.7 | 97.1 | 91.4 |
| sqlcoder-34b | 80 | 94.3 | 85.7 | 77.1 | 85.7 | 80 |
| gpt-4 | 64 | 94.3 | 88.6 | 74.2 | 85.7 | 80 |
| sqlcoder2-15b | 76 | 80 | 77.1 | 60 | 77.1 | 77.1 |
| sqlcoder-7b | 64 | 82.9 | 74.3 | 54.3 | 74.3 | 74.3 |
| gpt-3.5 | 68 | 77.1 | 74.2 | 34.3 | 65.7 | 71.4 |
| claude-2 | 52 | 71.4 | 74.3 | 57.1 | 65.7 | 62.9 |
Contact us on X at @defogdata, or on email at [email protected]