Instructions to use mlx-community/stablelm-2-1_6b-chat-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/stablelm-2-1_6b-chat-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir stablelm-2-1_6b-chat-4bit mlx-community/stablelm-2-1_6b-chat-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
metadata
language:
- en
license: other
tags:
- causal-lm
- mlx
datasets:
- HuggingFaceH4/ultrachat_200k
- allenai/ultrafeedback_binarized_cleaned
- meta-math/MetaMathQA
- WizardLM/WizardLM_evol_instruct_V2_196k
- openchat/openchat_sharegpt4_dataset
- LDJnr/Capybara
- Intel/orca_dpo_pairs
- hkust-nlp/deita-10k-v0
- teknium/OpenHermes-2.5
extra_gated_fields:
Name: text
Email: text
Country: text
Organization or Affiliation: text
I ALLOW Stability AI to email me about new model releases: checkbox
mlx-community/stablelm-2-1_6b-chat-4bit
This model was converted to MLX format from stabilityai/stablelm-2-1_6b-chat using mlx-lm version 0.8.0.
Model added by Prince Canuma.
Refer to the original model card for more details on the model.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/stablelm-2-1_6b-chat-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)