Text Generation
PEFT
Safetensors
English
lora
qwen2.5
sakthai
house-of-sak
tool-calling
function-calling
agent
qlora
conversational
assistant
Eval Results
Eval Results (legacy)
Instructions to use Nanthasit/sakthai-context-7b-tools with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Nanthasit/sakthai-context-7b-tools with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "Nanthasit/sakthai-context-7b-tools") - Notebooks
- Google Colab
- Kaggle
fix: update model family count from 13 to 12
Browse files
README.md
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| [embedding-multilingual](https://huggingface.co/Nanthasit/sakthai-embedding-multilingual) | 80 MB | Cross-lingual embeddings |
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| [tts-model](https://huggingface.co/Nanthasit/sakthai-tts-model) | 141 MB | Text-to-speech, 15 langs |
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## Links
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| [embedding-multilingual](https://huggingface.co/Nanthasit/sakthai-embedding-multilingual) | 80 MB | Cross-lingual embeddings |
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| [tts-model](https://huggingface.co/Nanthasit/sakthai-tts-model) | 141 MB | Text-to-speech, 15 langs |
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**12 models in the family · 8 datasets · 3 Spaces** — [full collection →](https://huggingface.co/collections/Nanthasit/sakthai-model-family-6a64745450b12d421c1f9f02)
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## Links
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