Downloads · 30 days
19
0% of all-time downloads
malhajar/Mistral-7B-v0.1-arabic
Mistral-7B-v0.1-arabic is a text generation model from malhajar. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
malhajar/Mistral-7B-Instruct-v0.2-turkish is a finetuned version of Mistral-7B-v0.1 using SFT Training and Freeze method. This model can answer information in a chat format as it is finetuned specifically on instructi…
Downloads · 30 days
19
0% of all-time downloads
All-time downloads
19.8K
Public
Parameters
7.2B
14.5 GB on disk
Likes
9
Public
Click a slice to open those files.
.safetensors14.5 GB · 100%
From the Hugging Face model README
malhajar/Mistral-7B-Instruct-v0.2-turkish is a finetuned version of Mistral-7B-v0.1 using SFT Training and Freeze method.
This model can answer information in a chat format as it is finetuned specifically on instructions specifically alpaca-gpt4-ar
Mohamad Alhajarmistralai/Mistral-7B-v0.1### Instruction:
<prompt> (without the <>)
### Response:
Use the code sample provided in the original post to interact with the model.
from transformers import AutoTokenizer,AutoModelForCausalLM
model_id = "malhajar/Mistral-7B-v0.1-arabic"
model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
device_map="auto",
torch_dtype=torch.float16,
revision="main")
tokenizer = AutoTokenizer.from_pretrained(model_id)
question: "ما هي الحياة؟"
# For generating a response
prompt = '''
### Instruction: {question} ### Response:
'''
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
output = model.generate(inputs=input_ids,max_new_tokens=512,pad_token_id=tokenizer.eos_token_id,top_k=50, do_sample=True,repetition_penalty=1.3
top_p=0.95,trust_remote_code=True,)
response = tokenizer.decode(output[0])
print(response)