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, )
File size: 493 Bytes
24f1cd9 307191b 24f1cd9 307191b 24f1cd9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ---
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) |