gguf endpoints_compatible region:us conversational
---
{}
---
Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


VinaLlama2-14B - GGUF
- Model creator: https://huggingface.co/vilm/
- Original model: https://huggingface.co/vilm/VinaLlama2-14B/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [VinaLlama2-14B.Q2_K.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q2_K.gguf) | Q2_K | 5.51GB |
| [VinaLlama2-14B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.IQ3_XS.gguf) | IQ3_XS | 6.03GB |
| [VinaLlama2-14B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.IQ3_S.gguf) | IQ3_S | 6.31GB |
| [VinaLlama2-14B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q3_K_S.gguf) | Q3_K_S | 6.31GB |
| [VinaLlama2-14B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.IQ3_M.gguf) | IQ3_M | 6.61GB |
| [VinaLlama2-14B.Q3_K.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q3_K.gguf) | Q3_K | 6.91GB |
| [VinaLlama2-14B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q3_K_M.gguf) | Q3_K_M | 6.91GB |
| [VinaLlama2-14B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q3_K_L.gguf) | Q3_K_L | 7.3GB |
| [VinaLlama2-14B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.IQ4_XS.gguf) | IQ4_XS | 7.37GB |
| [VinaLlama2-14B.Q4_0.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q4_0.gguf) | Q4_0 | 7.62GB |
| [VinaLlama2-14B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.IQ4_NL.gguf) | IQ4_NL | 7.68GB |
| [VinaLlama2-14B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q4_K_S.gguf) | Q4_K_S | 7.98GB |
| [VinaLlama2-14B.Q4_K.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q4_K.gguf) | Q4_K | 8.56GB |
| [VinaLlama2-14B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q4_K_M.gguf) | Q4_K_M | 8.56GB |
| [VinaLlama2-14B.Q4_1.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q4_1.gguf) | Q4_1 | 8.4GB |
| [VinaLlama2-14B.Q5_0.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q5_0.gguf) | Q5_0 | 9.18GB |
| [VinaLlama2-14B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q5_K_S.gguf) | Q5_K_S | 9.34GB |
| [VinaLlama2-14B.Q5_K.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q5_K.gguf) | Q5_K | 9.81GB |
| [VinaLlama2-14B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q5_K_M.gguf) | Q5_K_M | 9.81GB |
| [VinaLlama2-14B.Q5_1.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q5_1.gguf) | Q5_1 | 9.96GB |
| [VinaLlama2-14B.Q6_K.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q6_K.gguf) | Q6_K | 11.46GB |
| [VinaLlama2-14B.Q8_0.gguf](https://huggingface.co/RichardErkhov/vilm_-_VinaLlama2-14B-gguf/blob/main/VinaLlama2-14B.Q8_0.gguf) | Q8_0 | 14.03GB |




Original model description:
---
license: mit
language:
- vi
---
# VinaLlama2-14B Beta

GGUF Here: [VinaLlama2-14B-GGUF](https://huggingface.co/qnguyen3/14b-gguf)

**Top Features**:

- **Context Length**: 32,768 tokens.
- **VERY GOOD** at reasoning, mathematics and creative writing.
- Works with **Langchain Agent** out-of-the-box.

**Known Issues**
- Still a bit struggling with Vietnamese fact (Hoang Sa & Truong Sa, Historical questions).
- Hallucination when reasoning.
- Can't do Vi-En/En-Vi translation (yet)!

Quick use:

VRAM Requirement: ~20GB

```bash
pip install transformers accelerate
```

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
device = "cuda" # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained(
    "vilm/VinaLlama2-14B",
    torch_dtype='auto',
    device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("vilm/VinaLlama2-14B")

prompt = "Một cộng một bằng mấy?"
messages = [
    {"role": "system", "content": "Bạn là trợ lí AI hữu ích."},
    {"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
    messages,
    tokenize=False,
    add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)

generated_ids = model.generate(
    model_inputs.input_ids,
    max_new_tokens=1024,
    eos_token_id=tokenizer.eos_token_id,
    temperature=0.25,
)
generated_ids = [
    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]

response = tokenizer.batch_decode(generated_ids)[0]
print(response)
```

