Instructions to use varundevmishra09/My_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use varundevmishra09/My_Model with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for varundevmishra09/My_Model to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for varundevmishra09/My_Model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for varundevmishra09/My_Model to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="varundevmishra09/My_Model", max_seq_length=2048, )
| license: apache-2.0 | |
| base_model: mistralai/Mistral-7B-v0.1 | |
| tags: | |
| - mistral | |
| - fine-tuned | |
| - unsloth | |
| - text-generation | |
| pipeline_tag: text-generation | |
| # Mistral Fine-Tuned Model | |
| ## Description | |
| This is a fine-tuned version of Mistral 7B using Unsloth. | |
| ## Usage | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| model_id = "varundevmishra09/mistral-finetuned" | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| model = AutoModelForCausalLM.from_pretrained(model_id) |