Downloads · 30 days
80
4% of all-time downloads
RichardErkhov/ValiantLabs_-_Llama3.2-3B-Enigma-gguf
ValiantLabs_-_Llama3.2-3B-Enigma-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
80
4% of all-time downloads
All-time downloads
2.3K
Public
Repo size
38.1 GB
Likes
0
Public
Click a slice to open those files.
.gguf44.2 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
Llama3.2-3B-Enigma - GGUF
| Name | Quant method | Size |
|---|---|---|
| Llama3.2-3B-Enigma.Q2_K.gguf | Q2_K | 1.27GB |
| Llama3.2-3B-Enigma.IQ3_XS.gguf | IQ3_XS | 1.38GB |
| Llama3.2-3B-Enigma.IQ3_S.gguf | IQ3_S | 1.44GB |
| Llama3.2-3B-Enigma.Q3_K_S.gguf | Q3_K_S | 1.44GB |
| Llama3.2-3B-Enigma.IQ3_M.gguf | IQ3_M | 1.49GB |
| Llama3.2-3B-Enigma.Q3_K.gguf | Q3_K | 1.57GB |
| Llama3.2-3B-Enigma.Q3_K_M.gguf | Q3_K_M | 1.57GB |
| Llama3.2-3B-Enigma.Q3_K_L.gguf | Q3_K_L | 1.69GB |
| Llama3.2-3B-Enigma.IQ4_XS.gguf | IQ4_XS | 1.71GB |
| Llama3.2-3B-Enigma.Q4_0.gguf | Q4_0 | 1.79GB |
| Llama3.2-3B-Enigma.IQ4_NL.gguf | IQ4_NL | 1.79GB |
| Llama3.2-3B-Enigma.Q4_K_S.gguf | Q4_K_S | 1.8GB |
| Llama3.2-3B-Enigma.Q4_K.gguf | Q4_K | 1.88GB |
| Llama3.2-3B-Enigma.Q4_K_M.gguf | Q4_K_M | 1.88GB |
| Llama3.2-3B-Enigma.Q4_1.gguf | Q4_1 | 1.95GB |
| Llama3.2-3B-Enigma.Q5_0.gguf | Q5_0 | 2.11GB |
| Llama3.2-3B-Enigma.Q5_K_S.gguf | Q5_K_S | 2.11GB |
| Llama3.2-3B-Enigma.Q5_K.gguf | Q5_K | 2.16GB |
| Llama3.2-3B-Enigma.Q5_K_M.gguf | Q5_K_M | 2.16GB |
| Llama3.2-3B-Enigma.Q5_1.gguf | Q5_1 | 2.28GB |
| Llama3.2-3B-Enigma.Q6_K.gguf | Q6_K | 2.46GB |
| Llama3.2-3B-Enigma.Q8_0.gguf | Q8_0 | 3.19GB |
language:

Enigma is a code-instruct model built on Llama 3.2 3b.
This is the 2024-09-30 release of Enigma for Llama 3.2 3b, enhancing code-instruct and general chat capabilities.
Enigma is also available for Llama 3.1 8b!
Help us and recommend Enigma to your friends! We're excited for more Enigma releases in the future.
Enigma uses the Llama 3.2 Instruct prompt format. The example script below can be used as a starting point for general chat:
import transformers
import torch
model_id = "ValiantLabs/Llama3.2-3B-Enigma"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.bfloat16},
device_map="auto",
)
messages = [
{"role": "system", "content": "You are Enigma, a highly capable code assistant."},
{"role": "user", "content": "Can you explain virtualization to me?"}
]
outputs = pipeline(
messages,
max_new_tokens=1024,
)
print(outputs[0]["generated_text"][-1])
Enigma is built on top of Llama 3.2 3b Instruct, using high quality code-instruct data and general chat data in Llama 3.2 Instruct prompt style to supplement overall performance.
Our current version of Enigma is trained on code-instruct data from sequelbox/Tachibana and general chat data from sequelbox/Supernova.

Enigma is created by Valiant Labs.
Check out our HuggingFace page for Shining Valiant 2 and our other Build Tools models for creators!
Follow us on X for updates on our models!
We care about open source. For everyone to use.
We encourage others to finetune further from our models.
Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more quants, at much higher speed, than I would otherwise be able to.