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stable-code-3b by using the following code snippet:1import torch
2from transformers import AutoModelForCausalLM, AutoTokenizer
3tokenizer = AutoTokenizer.from_pretrained("stabilityai/stable-code-3b")
4model = AutoModelForCausalLM.from_pretrained(
5 "stabilityai/stable-code-3b",
6 torch_dtype="auto",
7)
8model.cuda()
9inputs = tokenizer("import torch\nimport torch.nn as nn", return_tensors="pt").to(model.device)
10tokens = model.generate(
11 **inputs,
12 max_new_tokens=48,
13 temperature=0.2,
14 do_sample=True,
15)
16print(tokenizer.decode(tokens[0], skip_special_tokens=True))1from transformers import AutoModelForCausalLM, AutoTokenizer
2tokenizer = AutoTokenizer.from_pretrained("stabilityai/stable-code-3b")
3model = AutoModelForCausalLM.from_pretrained(
4 "stabilityai/stable-code-3b",
5 torch_dtype="auto",
6 attn_implementation="flash_attention_2",
7)
8model.cuda()
9inputs = tokenizer("<fim_prefix>def fib(n):<fim_suffix> else:\n return fib(n - 2) + fib(n - 1)<fim_middle>", return_tensors="pt").to(model.device)
10tokens = model.generate(
11 **inputs,
12 max_new_tokens=48,
13 temperature=0.2,
14 do_sample=True,
15)
16print(tokenizer.decode(tokens[0], skip_special_tokens=True))1from transformers import AutoModelForCausalLM, AutoTokenizer
2tokenizer = AutoTokenizer.from_pretrained("stabilityai/stable-code-3b", trust_remote_code=True)
3model = AutoModelForCausalLM.from_pretrained(
4 "stabilityai/stable-code-3b",
5 trust_remote_code=True,
6 torch_dtype="auto",
7+ attn_implementation="flash_attention_2",
8)
9model.cuda()
10inputs = tokenizer("import torch\nimport torch.nn as nn", return_tensors="pt").to(model.device)
11tokens = model.generate(
12 **inputs,
13 max_new_tokens=48,
14 temperature=0.2,
15 do_sample=True,
16)
17print(tokenizer.decode(tokens[0], skip_special_tokens=True))