Instructions to use lingadevaruhp/thoshan_Flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lingadevaruhp/thoshan_Flash with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-9b-it-bnb-4bit") model = PeftModel.from_pretrained(base_model, "lingadevaruhp/thoshan_Flash") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Commit History
-
Upload model trained with Unsloth
Verified signatureUpload model trained with Unsloth 2x fasteraf5d834 -
Upload model trained with Unsloth
Verified signatureUpload model trained with Unsloth 2x faster7b3705b
-
Update README.md
Verified signaturefadbf7e
-
Upload 7 files
Verified signature66ae08e -
Update README.md
Verified signaturec74b424 -
Update README.md
Verified signatured8646d2 -
Update README.md
Verified signature# thoshan_Flash ## Model Description thoshan_Flash is a fine-tuned language model optimized for conversational AI and text generation tasks. This model has been specifically fine-tuned to provide enhanced performance in chat-based interactions and general text generation scenarios. ## Model Details - **Model Type**: Fine-tuned Language Model - **Training**: Custom fine-tuning on specialized datasets - **Use Cases**: Conversational AI, text generation, chat assistance - **License**: MIT ## Usage This model can be used for various text generation tasks including: - Conversational AI applications - Text completion and generation - Chat-based assistance - Creative writing support ## Training This model was fine-tuned using advanced techniques to improve its conversational abilities and text generation quality. ## Limitations As with all language models, users should be aware of potential biases and limitations in the generated content. Always review outputs for appropriateness in…0a51475 -
initial commit
Verified signature20665cc