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| Name | Quant method | Size |
|---|---|---|
| COKAL-v1-70B.Q2_K.gguf | Q2_K | 23.96GB |
| COKAL-v1-70B.IQ3_XS.gguf | IQ3_XS | 26.64GB |
| COKAL-v1-70B.IQ3_S.gguf | IQ3_S | 28.14GB |
| COKAL-v1-70B.Q3_K_S.gguf | Q3_K_S | 28.14GB |
| COKAL-v1-70B.IQ3_M.gguf | IQ3_M | 29.09GB |
| COKAL-v1-70B.Q3_K.gguf | Q3_K | 31.26GB |
| COKAL-v1-70B.Q3_K_M.gguf | Q3_K_M | 31.26GB |
| COKAL-v1-70B.Q3_K_L.gguf | Q3_K_L | 33.94GB |
| COKAL-v1-70B.IQ4_XS.gguf | IQ4_XS | 34.94GB |
| COKAL-v1-70B.Q4_0.gguf | Q4_0 | 36.5GB |
| COKAL-v1-70B.IQ4_NL.gguf | IQ4_NL | 36.86GB |
| COKAL-v1-70B.Q4_K_S.gguf | Q4_K_S | 36.86GB |
| COKAL-v1-70B.Q4_K.gguf | Q4_K | 38.88GB |
| COKAL-v1-70B.Q4_K_M.gguf | Q4_K_M | 38.88GB |
| COKAL-v1-70B.Q4_1.gguf | Q4_1 | 40.52GB |
| COKAL-v1-70B.Q5_0.gguf | Q5_0 | 44.53GB |
| COKAL-v1-70B.Q5_K_S.gguf | Q5_K_S | 44.53GB |
| COKAL-v1-70B.Q5_K.gguf | Q5_K | 45.73GB |
| COKAL-v1-70B.Q5_K_M.gguf | Q5_K_M | 45.73GB |
| COKAL-v1-70B.Q5_1.gguf | Q5_1 | 48.54GB |
| COKAL-v1-70B.Q6_K.gguf | Q6_K | 53.06GB |
| COKAL-v1-70B.Q8_0.gguf | Q8_0 | 68.72GB |
1
2from transformers import AutoModelForCausalLM, AutoTokenizer
3import torch
4
5repo = "DopeorNope/COKAL-v1_70B"
6model = AutoModelForCausalLM.from_pretrained(
7 repo,
8 return_dict=True,
9 torch_dtype=torch.float16,
10 device_map='auto'
11)
12model_tokenizer = AutoTokenizer.from_pretrained(repo)