File size: 1,334 Bytes
71eda90 4c629b9 71eda90 4c629b9 650152c 4c629b9 650152c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 |
---
license: apache-2.0
language:
- fa
---
### Installing Libraries
Make sure these libraries are installed correctly.
* ```pip install -q sentencepiece ```
* ```pip install -q transformers ```
* ```pip install -q accelerate ```
* ```pip install --upgrade -q bitsandbytes ```
```python
import torch
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer
model_path = "Neurai/llama7b"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
"Neurai/llama7b",
# load_in_8bit=True,
torch_dtype=torch.bfloat16,
low_cpu_mem_usage=True,
device_map="auto",
)
model.eval()
print('model loaded')
SYS_PROMPT = "زرافه چند سال عمر میکند؟"
def response_generate(input_prompt):
input_ids = tokenizer(input_prompt, return_tensors="pt")
outputs = model.generate(
inputs=input_ids["input_ids"].to("cuda"),
attention_mask=input_ids["attention_mask"].to("cuda"),
do_sample=True,
temperature=0.3,
top_k=50,
top_p=0.9,
max_new_tokens=512,
eos_token_id=tokenizer.eos_token_id,
pad_token_id=tokenizer.pad_token_id
)
response = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
return response
print(response_generate(f"{SYS_PROMPT}"))
```
|