Text Generation
PEFT
Safetensors
English
lora
qlora
sft
trl
text-to-sql
sql
conversational
Eval Results (legacy)
Instructions to use SASVAAI/GLM-4.7-Flash-sql-create-context with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SASVAAI/GLM-4.7-Flash-sql-create-context with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("zai-org/GLM-4.7-Flash") model = PeftModel.from_pretrained(base_model, "SASVAAI/GLM-4.7-Flash-sql-create-context") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from SASVAAI/GLM-4.7-Flash-sql-create-context: direct link, hf CLI and curl.
- Browser
- Download file 136 Bytes
-
https://huggingface.co/SASVAAI/GLM-4.7-Flash-sql-create-context/resolve/main/eval_results.json
- Command line
-
hf download hf://SASVAAI/GLM-4.7-Flash-sql-create-context/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/SASVAAI/GLM-4.7-Flash-sql-create-context/resolve/main/eval_results.json
136 Bytes
| { | |
| "metrics": { | |
| "exact_match": 0.805, | |
| "bleu": 0.9400823275452048, | |
| "rouge_l": 0.9860549005631489 | |
| }, | |
| "num_samples": 400 | |
| } |