mav23 commited on
Commit
a0129c3
1 Parent(s): 7171f9d

Upload folder using huggingface_hub

Browse files
Files changed (3) hide show
  1. .gitattributes +1 -0
  2. README.md +67 -0
  3. reasoning-0.5b.Q4_0.gguf +3 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ reasoning-0.5b.Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,67 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-0.5B-Instruct
3
+ language:
4
+ - en
5
+ license: apache-2.0
6
+ datasets:
7
+ - KingNish/reasoning-base-20k
8
+ tags:
9
+ - text-generation-inference
10
+ - transformers
11
+ - unsloth
12
+ - qwen2
13
+ - trl
14
+ - sft
15
+ - reasoning
16
+ ---
17
+
18
+
19
+ # Model Dexcription
20
+
21
+ It's First iteration of this model. For testing purpose its just trained on 10k rows.
22
+ It performed very well than expected. It do first reasoning and than generate response on based on it but it do like o1.
23
+ It do reasoning separately no special tokens or in response reasoning.
24
+ Below is inference code.
25
+ ```python
26
+ from transformers import AutoModelForCausalLM, AutoTokenizer
27
+
28
+ MAX_REASONING_TOKENS = 1024
29
+ MAX_RESPONSE_TOKENS = 512
30
+
31
+ model_name = "KingNish/Reasoning-0.5b"
32
+
33
+ model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
34
+ tokenizer = AutoTokenizer.from_pretrained(model_name)
35
+
36
+ prompt = "Which is greater 9.9 or 9.11 ??"
37
+ messages = [
38
+ {"role": "user", "content": prompt}
39
+ ]
40
+
41
+ # Generate reasoning
42
+ reasoning_template = tokenizer.apply_chat_template(messages, tokenize=False, add_reasoning_prompt=True)
43
+ reasoning_inputs = tokenizer(reasoning_template, return_tensors="pt").to(model.device)
44
+ reasoning_ids = model.generate(**reasoning_inputs, max_new_tokens=MAX_REASONING_TOKENS)
45
+ reasoning_output = tokenizer.decode(reasoning_ids[0, reasoning_inputs.input_ids.shape[1]:], skip_special_tokens=True)
46
+
47
+ # print("REASONING: " + reasoning_output)
48
+
49
+ # Generate answer
50
+ messages.append({"role": "reasoning", "content": reasoning_output})
51
+ response_template = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
52
+ response_inputs = tokenizer(response_template, return_tensors="pt").to(model.device)
53
+ response_ids = model.generate(**response_inputs, max_new_tokens=MAX_RESPONSE_TOKENS)
54
+ response_output = tokenizer.decode(response_ids[0, response_inputs.input_ids.shape[1]:], skip_special_tokens=True)
55
+
56
+ print("ANSWER: " + response_output)
57
+ ```
58
+
59
+ - **Trained by:** [Nishith Jain](https://huggingface.co/KingNish)
60
+ - **License:** apache-2.0
61
+ - **Finetuned from model :** [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct)
62
+ - **Dataset used :** [KingNish/reasoning-base-20k](https://huggingface.co/datasets/KingNish/reasoning-base-20k)
63
+
64
+
65
+ This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
66
+
67
+ [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
reasoning-0.5b.Q4_0.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2a851d1a0e9842faa355d91ba02b719c78c830b0de029759d09f90e13bde80a8
3
+ size 352152832