How to use from
Unsloth StudioInstall 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 DrishtiSharma/mistral-7b-bnb-4bit-dolly-15k-english-unsloth-w-packing to start chattingUsing HuggingFace Spaces for Unsloth
# No setup required# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DrishtiSharma/mistral-7b-bnb-4bit-dolly-15k-english-unsloth-w-packing to start chattingLoad model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="DrishtiSharma/mistral-7b-bnb-4bit-dolly-15k-english-unsloth-w-packing",
max_seq_length=2048,
)Quick Links
mistral-7b-bnb-4bit-base-dolly-15k-english-unsloth-w-packing
This model is a fine-tuned version of unsloth/mistral-7b-bnb-4bit on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.3099
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 6
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3157 | 0.68 | 100 | 1.2756 |
| 1.2042 | 1.36 | 200 | 1.2755 |
| 1.1548 | 2.04 | 300 | 1.2928 |
| 1.0348 | 2.72 | 400 | 1.3099 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
- Downloads last month
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Base model
unsloth/mistral-7b-bnb-4bit
Install Unsloth Studio (macOS, Linux, WSL)
# Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DrishtiSharma/mistral-7b-bnb-4bit-dolly-15k-english-unsloth-w-packing to start chatting