Update model card for Afrikaans

README.md

@@ -1,47 +1,104 @@
----
-language: afr
-license: apache-2.0
-tags:
-  - trimmed
-  - qwen3
-base_model: Qwen/Qwen3-0.6B
-base_model_relation: quantized
-datasets:
-  - Lumberjackk/fineweb-2-trimming
----
-
-# Qwen3-0.6B-afr-32768
-
-This model is a **32.47% smaller** version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) optimized for Afrikaans via vocabulary size reduction ([trimming](https://huggingface.co/blog/introduction-to-trimming)).
-
-| Metric | Original | Trimmed | Reduction |
-|--------|----------|---------|-----------|
-| **Vocabulary size** | 151,643 | 32,768 | **78.39%** |
-| **Parameters** | 751,632,384 | 507,576,320 | **32.47%** |
-
-## Usage
-
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-tokenizer = AutoTokenizer.from_pretrained("AlphaEdge-AI/Qwen3-0.6B-afr-32768")
-model = AutoModelForCausalLM.from_pretrained("AlphaEdge-AI/Qwen3-0.6B-afr-32768", torch_dtype="auto", device_map="auto")
-
-prompt = "Your prompt in Afrikaans."
-messages = [{"role": "user", "content": prompt}]
-text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True, enable_thinking=True)
-model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
-
-generated_ids = model.generate(**model_inputs, max_new_tokens=32768)
-output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
-
-try:
-    index = len(output_ids) - output_ids[::-1].index(32767)
-except ValueError:
-    index = 0
-
-thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
-content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
-print("thinking:", thinking_content)
-print("content:", content)
-```
+---
+pipeline_tag: text-generation
+language: afr
+license: apache-2.0
+tags:
+  - trimmed
+library_name: transformers
+base_model: Qwen3-0.6B
+base_model_relation: quantized
+datasets:
+  - lbourdois/fineweb-2-trimming
+---
+
+# Qwen3-0.6B-afr-32768
+This model is a **32.47% smaller** version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) optimized for **Afrikaans** language via vocabulary size reduction using the [trimming](https://huggingface.co/blog/lbourdois/introduction-to-trimming) method.  
+This trimmed model should perform similarly to the original model with only 32,768 tokens and a much smaller memory footprint. However, it may not perform well for other languages as tokens not commonly used in the selected languages were removed from the vocabulary.
+
+## Model Statistics
+| Metric | Original | Trimmed | Reduction |
+|--------|----------|---------|-----------|
+| **Vocabulary size** | 151,936 tokens | 32,768 tokens | **78.43%** |
+| **Model size** | 751,632,384 params | 507,576,320 params | **32.47%** |
+
+![image](https://raw.githubusercontent.com/lbourdois/blog/refs/heads/master/assets/images/Trimming/qwen3-0.6B-32768.png)
+
+## Mining Dataset Statistics
+- **Number of texts used for mining**: 200,000 texts  
+- **Dataset**: [lbourdois/fineweb-2-trimming](https://huggingface.co/datasets/lbourdois/fineweb-2-trimming)
+
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "alphaedge-ai/Qwen3-0.6B-afr-32768"
+
+# load the tokenizer and the model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+
+# prepare the model input
+prompt = "Your prompt in Afrikaans."
+messages = [
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True,
+    enable_thinking=True # Switches between thinking and non-thinking modes. Default is True.
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+# conduct text completion
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=32768
+)
+output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist() 
+
+# parsing thinking content
+try:
+    # rindex finding 32767 (</think>)
+    index = len(output_ids) - output_ids[::-1].index(32767)
+except ValueError:
+    index = 0
+
+thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("
+")
+content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("
+")
+
+print("thinking content:", thinking_content)
+print("content:", content)
+
+```
+
+## Citations
+
+#### Qwen3
+```
+@misc{qwen3technicalreport,
+      title={Qwen3 Technical Report}, 
+      author={Qwen Team},
+      year={2025},
+      eprint={2505.09388},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2505.09388}, 
+}
+```
+
+#### Trimming blog post
+```
+@misc{hf_blogpost_trimming,
+      title={Introduction to Trimming}, 
+      author={Loïck BOURDOIS and Tom AARSEN and Bram VANROY and Christopher AKIKI and Woojun JUNG and Manuel ROMERO and Prithiv SAKTHI},
+      year={2026},
+      url={https://huggingface.co/blog/lbourdois/introduction-to-trimming}, 
+}
+```