---
library_name: transformers
license: other
license_name: eva-llama3.3
base_model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0
tags:
- generated_from_trainer
- mlx
datasets:
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- Nopm/Opus_WritingStruct
- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
- Gryphe/Sonnet3.5-Charcard-Roleplay
- Gryphe/ChatGPT-4o-Writing-Prompts
- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
- nothingiisreal/Reddit-Dirty-And-WritingPrompts
- allura-org/Celeste-1.x-data-mixture
- cognitivecomputations/dolphin-2.9.3
model-index:
- name: dev/shm/EVA-LLaMA-3.33-70B-v0.1
  results: []
---

# shanginn/EVA-UNIT-01-EVA-LLaMA-3.33-70B-v0.0-q4

The Model [shanginn/EVA-UNIT-01-EVA-LLaMA-3.33-70B-v0.0-q4](https://huggingface.co/shanginn/EVA-UNIT-01-EVA-LLaMA-3.33-70B-v0.0-q4) was converted to MLX format from [EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0](https://huggingface.co/EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0) using mlx-lm version **0.19.2**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("shanginn/EVA-UNIT-01-EVA-LLaMA-3.33-70B-v0.0-q4")

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)
```