Text Generation
MLX
Safetensors
progen
progen2
protein-language-model
mlx-lm
bfloat16
icl-many-replication
custom_code
Instructions to use N8Programs/ProGen2-base-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use N8Programs/ProGen2-base-bf16 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("N8Programs/ProGen2-base-bf16") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use N8Programs/ProGen2-base-bf16 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "N8Programs/ProGen2-base-bf16" --prompt "Once upon a time"
File size: 1,438 Bytes
e8df098 3515095 e8df098 | 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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | ---
license: bsd-3-clause
library_name: mlx
pipeline_tag: text-generation
base_model: hugohrban/progen2-base
tags:
- progen
- progen2
- protein-language-model
- mlx
- mlx-lm
- safetensors
- bfloat16
- icl-many-replication
widget:
- text: 1MEVVIVTGMSGAGK
- text: 1MKTLLILAV
---
# ProGen2 Base BF16 MLX Conversion
This repository contains a BF16 MLX-LM conversion of
[`hugohrban/progen2-base`](https://huggingface.co/hugohrban/progen2-base), a
mirror of the base ProGen2 model by Nijkamp et al.
The source checkpoint was downloaded from Hugging Face revision
`71228cbfca5960f9fab5775f378bba3673af9f00` and converted from FP32 to BF16
safetensors. The converted tensor file contains 764,803,616 BF16 parameters.
This conversion was prepared for the standalone replication artifact for
*Many Next Token Predictors are In-context Learners*.
## Files
- `model.safetensors`: BF16 converted ProGen2-base weights.
- `progen2_mlx.py`: MLX-LM custom model implementation.
- `config.json`, tokenizer files, and ProGen custom-code files copied from the
source model with the MLX model-file entry added.
## Loading with MLX-LM
```python
from mlx_lm import load
model, tokenizer = load("N8Programs/ProGen2-base-bf16")
```
## Original Model
Please cite and follow the terms of the upstream ProGen2 work and the source
model repository:
- Source model: https://huggingface.co/hugohrban/progen2-base
- Paper: https://arxiv.org/abs/2206.13517
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