ubermenchh
/

Qwen2.5-3B-open-r1-math

@@ -1,202 +1,124 @@
 ---
-library_name: transformers
 tags:
 - unsloth
 - trl
 - grpo
 ---
-# Model Card for Model ID
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 ---
+base_model: unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
 tags:
+- text-generation-inference
+- transformers
 - unsloth
+- qwen2
 - trl
 - grpo
+license: apache-2.0
+language:
+- en
+datasets:
+- open-r1/OpenR1-Math-220k
 ---
+This is my experiment with training a reasoning model using TRL's GRPO and Unsloth API.
+# Inference:
+## Using Unsloth API (For Faster Inference):
+```
+import torch
+from unsloth import FastLanguageModel
+from transformers import TextStreamer
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "ubermenchh/Qwen2.5-3B-open-r1-math",
+    max_seq_length = 1024,
+    dtype = torch.bfloat16,
+    load_in_4bit = True,
+)
+FastLanguageModel.for_inference(model)
+SYSTEM_PROMPT = """
+Respond in the following format:
+<think>
+...
+</think>
+<answer>
+...
+</answer>
+"""
+test_question = """
+Let $z \in \mathbf{C}$, satisfying the condition $a z^{n}+b \mathrm{i} z^{n-1}+b \mathrm{i} z-a=0, a, b \in \mathbf{R}, m \in$ $\mathbf{N}$, find $|z|$.
+"""
+messages = [
+    {"role": "system", "content": SYSTEM_PROMPT},
+    {"role": "user", "content": test_question},
+]
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt = True,
+    return_tensors = "pt",
+).to("cuda")
+text_streamer = TextStreamer(tokenizer, skip_prompt = True)
+_ = model.generate(input_ids, streamer = text_streamer, max_new_tokens = 2048, pad_token_id = tokenizer.eos_token_id)
+```
+## Using Transformers API:
+```
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+model = AutoModelForCausalLM.from_pretrained(
+  "ubermenchh/Qwen2.5-3B-open-r1-math",
+  torch_dtype=torch.bfloat16,
+  device_map="auto",
+  trust_remote_code=True
+)
+tokenizer = AutoTokenizer.from_pretrained(
+  "ubermenchh/Qwen2.5-3B-open-r1-math",
+  trust_remote_code=True
+)
+SYSTEM_PROMPT = """
+Respond in the following format:
+<think>
+...
+</think>
+<answer>
+...
+</answer>
+"""
+problem = "Let $z \in \mathbf{C}$, satisfying the condition $a z^{n}+b \mathrm{i} z^{n-1}+b \mathrm{i} z-a=0, a, b \in \mathbf{R}, m \in$ $\mathbf{N}$, find $|z|$."
+prompt = [
+    {"role": "system", "content": SYSTEM_PROMPT},
+    {"role": "user", "content": problem}
+]
+input_text = tokenizer.apply_chat_template(prompt, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(input_text, return_tensors="pt").to(model.device)
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=3000,
+    temperature=1.3,
+    num_return_sequences=1,
+    pad_token_id=tokenizer.pad_token_id,
+    eos_token_id=tokenizer.eos_token_id
+)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print("Question:\n", problem)
+print("\n\nResponse:\n", response)
+```
+## References:
+- [https://github.com/HarleyCoops/smolThinker-.5B](https://github.com/HarleyCoops/smolThinker-.5B)
+- [https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb](https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb)
+- [https://github.com/huggingface/open-r1](https://github.com/huggingface/open-r1)
+# Uploaded  model
+- **Developed by:** ubermenchh
+- **License:** apache-2.0
+- **Finetuned from model :** unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
+This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)