iamtarun/python_code_instructions_18k_alpaca
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How to use Vo1dAbyss/DeepSeek-R1-Distill-Qwen-7B-Python-4bit-V2 with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Vo1dAbyss/DeepSeek-R1-Distill-Qwen-7B-Python-4bit-V2", dtype="auto")How to use Vo1dAbyss/DeepSeek-R1-Distill-Qwen-7B-Python-4bit-V2 with Unsloth Studio:
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 Vo1dAbyss/DeepSeek-R1-Distill-Qwen-7B-Python-4bit-V2 to start chatting
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 Vo1dAbyss/DeepSeek-R1-Distill-Qwen-7B-Python-4bit-V2 to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Vo1dAbyss/DeepSeek-R1-Distill-Qwen-7B-Python-4bit-V2 to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="Vo1dAbyss/DeepSeek-R1-Distill-Qwen-7B-Python-4bit-V2",
max_seq_length=2048,
)A finetuned model trained on 5 datasets with a total of 876000 rows. This model was an experiment, as I wanted to train a model with a lot of python code and see the results.
This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.