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| Name | Quant method | Size |
|---|---|---|
| TowerBase-7B-v0.1.Q2_K.gguf | Q2_K | 2.36GB |
| TowerBase-7B-v0.1.IQ3_XS.gguf | IQ3_XS | 2.6GB |
| TowerBase-7B-v0.1.IQ3_S.gguf | IQ3_S | 2.75GB |
| TowerBase-7B-v0.1.Q3_K_S.gguf | Q3_K_S | 2.75GB |
| TowerBase-7B-v0.1.IQ3_M.gguf | IQ3_M | 2.9GB |
| TowerBase-7B-v0.1.Q3_K.gguf | Q3_K | 3.07GB |
| TowerBase-7B-v0.1.Q3_K_M.gguf | Q3_K_M | 3.07GB |
| TowerBase-7B-v0.1.Q3_K_L.gguf | Q3_K_L | 3.35GB |
| TowerBase-7B-v0.1.IQ4_XS.gguf | IQ4_XS | 3.4GB |
| TowerBase-7B-v0.1.Q4_0.gguf | Q4_0 | 3.56GB |
| TowerBase-7B-v0.1.IQ4_NL.gguf | IQ4_NL | 3.58GB |
| TowerBase-7B-v0.1.Q4_K_S.gguf | Q4_K_S | 3.59GB |
| TowerBase-7B-v0.1.Q4_K.gguf | Q4_K | 3.8GB |
| TowerBase-7B-v0.1.Q4_K_M.gguf | Q4_K_M | 3.8GB |
| TowerBase-7B-v0.1.Q4_1.gguf | Q4_1 | 3.95GB |
| TowerBase-7B-v0.1.Q5_0.gguf | Q5_0 | 4.33GB |
| TowerBase-7B-v0.1.Q5_K_S.gguf | Q5_K_S | 4.33GB |
| TowerBase-7B-v0.1.Q5_K.gguf | Q5_K | 4.45GB |
| TowerBase-7B-v0.1.Q5_K_M.gguf | Q5_K_M | 4.45GB |
| TowerBase-7B-v0.1.Q5_1.gguf | Q5_1 | 4.72GB |
| TowerBase-7B-v0.1.Q6_K.gguf | Q6_K | 5.15GB |
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_id = "Unbabel/TowerBase-7B-v0.1"
4tokenizer = AutoTokenizer.from_pretrained(model_id)
5
6model = AutoModelForCausalLM.from_pretrained(model_id)
7
8text = "English: My name is TowerBase.\nPortuguese:"
9inputs = tokenizer(text, return_tensors="pt")
10
11outputs = model.generate(**inputs, max_new_tokens=20)
12print(tokenizer.decode(outputs[0], skip_special_tokens=True))1@misc{tower_llm_2024,
2 title={Tower: An Open Multilingual Large Language Model for Translation-Related Tasks},
3 author={Duarte M. Alves and José Pombal and Nuno M. Guerreiro and Pedro H. Martins and João Alves and Amin Farajian and Ben Peters and Ricardo Rei and Patrick Fernandes and Sweta Agrawal and Pierre Colombo and José G. C. de Souza and André F. T. Martins},
4 year={2024},
5 eprint={2402.17733},
6 archivePrefix={arXiv},
7 primaryClass={cs.CL}
8}