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, )
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# Mistral Fine-Tuned Model
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## Description
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## Usage
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_id = "varundevmishra09/mistral-finetuned"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id)
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## Notes
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- Fine-tuned using LoRA
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- Merged into full model
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---
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license: apache-2.0
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base_model: mistralai/Mistral-7B-v0.1
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tags:
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- mistral
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- fine-tuned
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- unsloth
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- text-generation
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pipeline_tag: text-generation
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---
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# Mistral Fine-Tuned Model
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## Description
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_id = "varundevmishra09/mistral-finetuned"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id)
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