RichardErkhov commited on
Commit
e9c01b9
·
verified ·
1 Parent(s): 85f2e70

uploaded readme

Browse files
Files changed (1) hide show
  1. README.md +85 -0
README.md ADDED
@@ -0,0 +1,85 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Quantization made by Richard Erkhov.
2
+
3
+ [Github](https://github.com/RichardErkhov)
4
+
5
+ [Discord](https://discord.gg/pvy7H8DZMG)
6
+
7
+ [Request more models](https://github.com/RichardErkhov/quant_request)
8
+
9
+
10
+ LlamaXCoder-3.2-3B-Instruct - AWQ
11
+ - Model creator: https://huggingface.co/motexture/
12
+ - Original model: https://huggingface.co/motexture/LlamaXCoder-3.2-3B-Instruct/
13
+
14
+
15
+
16
+
17
+ Original model description:
18
+ ---
19
+ license: apache-2.0
20
+ datasets:
21
+ - motexture/cData
22
+ language:
23
+ - en
24
+ - it
25
+ - es
26
+ base_model:
27
+ - meta-llama/Llama-3.2-3B-Instruct
28
+ pipeline_tag: text-generation
29
+ tags:
30
+ - coding
31
+ - coder
32
+ - model
33
+ - llama
34
+ ---
35
+
36
+ # LlamaXCoder-3.2-3B-Instruct
37
+
38
+ ## Introduction
39
+
40
+ LlamaXCoder-3.2-3B-Instruct is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct, trained on the cData coding dataset to improve its reasoning and coding ability.
41
+
42
+ ## Quickstart
43
+
44
+ Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
45
+
46
+ ```python
47
+ from transformers import AutoModelForCausalLM, AutoTokenizer
48
+ device = "cuda" # the device to load the model onto
49
+
50
+ model = AutoModelForCausalLM.from_pretrained(
51
+ "motexture/LlamaXCoder-3.2-3B-Instruct",
52
+ torch_dtype="auto",
53
+ device_map="auto"
54
+ )
55
+ tokenizer = AutoTokenizer.from_pretrained("motexture/LlamaXCoder-3.2-3B-Instruct")
56
+
57
+ prompt = "Write a C++ program that prints Hello World!"
58
+ messages = [
59
+ {"role": "system", "content": "You are a helpful assistant."},
60
+ {"role": "user", "content": prompt}
61
+ ]
62
+ text = tokenizer.apply_chat_template(
63
+ messages,
64
+ tokenize=False,
65
+ add_generation_prompt=True
66
+ )
67
+ model_inputs = tokenizer([text], return_tensors="pt").to(device)
68
+
69
+ generated_ids = model.generate(
70
+ model_inputs.input_ids,
71
+ max_new_tokens=4096,
72
+ do_sample=True,
73
+ temperature=0.3
74
+ )
75
+ generated_ids = [
76
+ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
77
+ ]
78
+
79
+ response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
80
+ ```
81
+
82
+ ## License
83
+
84
+ [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
85
+