Views
No views yet
| 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 |

1import transformers
2import torch
3
4model_id = "ValiantLabs/Llama3.2-3B-Enigma"
5
6pipeline = transformers.pipeline(
7 "text-generation",
8 model=model_id,
9 model_kwargs={"torch_dtype": torch.bfloat16},
10 device_map="auto",
11)
12
13messages = [
14 {"role": "system", "content": "You are Enigma, a highly capable code assistant."},
15 {"role": "user", "content": "Can you explain virtualization to me?"}
16]
17
18outputs = pipeline(
19 messages,
20 max_new_tokens=1024,
21)
22
23print(outputs[0]["generated_text"][-1])