Update README.md

README.md

@@ -1,14 +1,57 @@
----
-language:
-- zh
-- bo
-- en
-base_model:
-- meta-llama/Meta-Llama-3-8B-Instruct
-pipeline_tag: text-generation
----
+---
+language:
+- zh
+- bo
+- en
+base_model:
+- meta-llama/Meta-Llama-3-8B-Instruct
+pipeline_tag: text-generation
+---
 # TibetaMind: Advanced Tibetan Language Model
 **TibetaMind** is an advanced language model based on the Llama 3-8B-Instruct architecture, further fine-tuned using extensive Tibetan language corpora. Through this specialized fine-tuning, **TibetaMind** has significantly enhanced its ability to comprehend, process, and generate Tibetan language content, while also providing seamless cross-language understanding between Tibetan and Chinese. This allows for accurate translation and communication across these languages. **TibetaMind** can be applied to a variety of tasks, including Tibetan text generation, summarization, and translation between Tibetan and Chinese, playing a pivotal role in preserving and advancing Tibetan linguistics in the digital age.
 
+# How to use
 
-##
+## Use with transformers
+
+### Transformers AutoModelForCausalLM
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "DaydreamerF/TibetaMind"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+messages = [
+    {"role": "user", "content": "如何用藏语表达下面汉语的意思：汉语句子：大狗在楼里不好养。"},
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+response = outputs[0][input_ids.shape[-1]:]
+print(tokenizer.decode(response, skip_special_tokens=True))
+```