feat: add how to

README.md

@@ -6,19 +6,72 @@ tags:
 model-index:
 - name: trial2
   results: []
+license: apache-2.0
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
 
-## Model description
+## mistral-2b-base
 
-More information needed
+Welcome to my model card!
+
+This Model feature is ...
+
+- trained by japanese
+- trained in two stages: patch level and token level
+- Suppression of unknown word generation by using byte fallback in SentencePiece tokenizer and conversion to huggingface Tokenizers format
+- Use of Mistral 2B
 
-## Intended uses & limitations
+Yukkuri shite ittene!
+
+<!-- ## Intended uses & limitations
 
 More information needed
+ -->
+
+## How to use the model
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+import torch
+
+MODEL_NAME = "ce-lery/mistral-2b-base"
+torch.set_float32_matmul_precision('high')
+
+device = "cuda"
+if (device != "cuda" and device != "cpu"):
+    device = "cpu"
+
+tokenizer = AutoTokenizer.from_pretrained(model_path,use_fast=False)
+model = AutoModelForCausalLM.from_pretrained(model_path,
+                                             trust_remote_code=True,
+                                             ).to(device)
+
+
+prompt = "自然言語処理とは、"
+
+inputs = tokenizer(prompt, add_special_tokens=True,return_tensors="pt").to(model.device)
+with torch.no_grad():
+
+    outputs = model.generate(
+        inputs["input_ids"],
+        max_new_tokens=4096,
+        do_sample=True,
+        early_stopping=False,
+        top_p=0.95,
+        top_k=50,
+        temperature=0.7,
+        no_repeat_ngram_size=2,
+        num_beams=3
+    )
+
+print(outputs.tolist()[0])
+outputs_txt = tokenizer.decode(outputs[0])
+print(outputs_txt)
+
+```
 
 ## Training and evaluation data
 
@@ -26,6 +79,8 @@ More information needed
 
 ## Training procedure
 
+
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -42,6 +97,7 @@ The following hyperparameters were used during training:
 
 ### Training results
 
+Please refer [here]().
 
 
 ### Framework versions
@@ -49,4 +105,4 @@ The following hyperparameters were used during training:
 - Transformers 4.46.2
 - Pytorch 2.4.0a0+f70bd71a48.nv24.06
 - Datasets 2.20.0
-- Tokenizers 0.20.3
+- Tokenizers 0.20.3