license: apache-2.0 | |
library_name: transformers | |
language: | |
- en | |
- zh | |
pipeline_tag: text-generation | |
base_model: sthenno-com/miscii-14b-1028 | |
tags: | |
- chat | |
- conversational | |
- custom-research | |
- mlx | |
model-index: | |
- name: miscii-14b-1028 | |
results: | |
- task: | |
type: text-generation | |
dataset: | |
name: MMLU-PRO (5-shot) | |
type: TIGER-Lab/MMLU-Pro | |
config: main | |
split: test | |
args: | |
num_few_shot: 5 | |
metrics: | |
- type: exact-match | |
value: 0.6143 | |
name: exact_match | |
# mlx-community/miscii-14b-1028-4bit | |
The Model [mlx-community/miscii-14b-1028-4bit](https://huggingface.co/mlx-community/miscii-14b-1028-4bit) was converted to MLX format from [sthenno-com/miscii-14b-1028](https://huggingface.co/sthenno-com/miscii-14b-1028) using mlx-lm version **0.19.3**. | |
## Use with mlx | |
```bash | |
pip install mlx-lm | |
``` | |
```python | |
from mlx_lm import load, generate | |
model, tokenizer = load("mlx-community/miscii-14b-1028-4bit") | |
prompt="hello" | |
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None: | |
messages = [{"role": "user", "content": prompt}] | |
prompt = tokenizer.apply_chat_template( | |
messages, tokenize=False, add_generation_prompt=True | |
) | |
response = generate(model, tokenizer, prompt=prompt, verbose=True) | |
``` | |