metadata
language:
- ja
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- trl
- mistral
datasets:
- sakusakumura/databricks-dolly-15k-ja-scored
- llm-jp/oasst1-21k-ja
- nu-dialogue/jmultiwoz
- kunishou/amenokaku-code-instruct
license_name: mistral
base_model: tokyotech-llm/Swallow-MS-7b-v0.1
Uploaded model
- Developed by: taoki
- License: apache-2.0
- Finetuned from model : tokyotech-llm/Swallow-MS-7b-v0.1
Usage
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained(
"taoki/Swallow-MS-7b-v0.1-qlora-oasst1-jmultiwoz-dolly-amenokaku"
)
model = AutoModelForCausalLM.from_pretrained(
"taoki/Swallow-MS-7b-v0.1-qlora-oasst1-jmultiwoz-dolly-amenokaku"
)
if torch.cuda.is_available():
model = model.to("cuda")
prompt="[INST] ไปๆฅใฏ4/1ใชใฎใงใใใๅจใใฎ็ใใใ็ชๆๅญใใชใใใจใ่จใฃใฆใใฆๅฐๆใใฆใใพใใไธไฝไฝใ่ตทใใฃใฆใใใฎใงใใใใ๏ผ [/INST]\n"
input_ids = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(
**input_ids,
max_new_tokens=512,
do_sample=True,
top_p=0.95,
temperature=0.1,
repetition_penalty=1.1,
)
print(tokenizer.decode(outputs[0]))
Output
<s> [INST] ไปๆฅใฏ4/1ใชใฎใงใใใๅจใใฎ็ใใใ็ชๆๅญใใชใใใจใ่จใฃใฆใใฆๅฐๆใใฆใใพใใไธไฝไฝใ่ตทใใฃใฆใใใฎใงใใใใ๏ผ [/INST]
4ๆ1ๆฅใฏใจใคใใชใซใใผใซใงใไบบใ
ใฏๅ่ซใใใใใใ่จใฃใฆๆฅฝใใๆฅใจใใใฆใใพใใใใฎ็ฟๆ
ฃใฏใ1564ๅนดใซใใฉใณในใฎใทใฃใซใซ9ไธใ4ๆ1ๆฅใซ็ตๅฉใใใใจใใๅงใพใฃใใจ่จใใใฆใใใ
ใใใใใใชใใๅฐๆใใฆใใใฎใชใใใใใฏใใใใใใใชใใๅ่ซใใใใใใ่จใฃใฆใใไบบใใกใใใใชใใใใฎใใใชใใฎใ ใจๆใฃใฆใใชใใใจใ่จใฃใฆใใใใใ ใจๆใใพใใใใใฏใๅฝผใใใใชใใ้ฉใใใใใ็ฌใใใใใใใใใซๅใใคใใฆใใๅฏ่ฝๆงใใใใใจใๆๅณใใพใใ
ใใ่ชฐใใใใชใใๅฐๆใใใใใไธๅฟซใซใใใใใใใใใชใใจใ่จใฃใๅ ดๅใฏใๆฐใซใใ็ก่ฆใใฆใใ ใใใใพใใ่ชๅ่ช่บซใไปไบบใๅทใคใใใใใชๅใใคใใใจใฏ้ฟใใพใใใใ</s>
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.