Update README.md
Browse files
README.md
CHANGED
@@ -1,4 +1,100 @@
|
|
1 |
---
|
2 |
-
license:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
library_name: transformers
|
4 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
---
|
2 |
+
license: other
|
3 |
+
license_name: helpingai
|
4 |
+
license_link: https://helpingai.co/license
|
5 |
+
pipeline_tag: text-generation
|
6 |
+
language:
|
7 |
+
- en
|
8 |
+
tags:
|
9 |
+
- HelpingAI
|
10 |
+
- Emotionally-Intelligent
|
11 |
+
- EQ-focused
|
12 |
+
- Conversational
|
13 |
+
- SLM
|
14 |
library_name: transformers
|
15 |
+
---
|
16 |
+
|
17 |
+
# HelpingAI3
|
18 |
+
|
19 |
+
## Model Description
|
20 |
+
|
21 |
+
**HelpingAI3** is an advanced language model developed to excel in emotionally intelligent conversations. Building upon the foundations of HelpingAI2.5, this model offers enhanced emotional understanding and contextual awareness.
|
22 |
+
|
23 |
+
## Model Details
|
24 |
+
|
25 |
+
- **Developed by**: HelpingAI
|
26 |
+
- **Model type**: Decoder-only large language model
|
27 |
+
- **Language**: English
|
28 |
+
- **License**: [HelpingAI License](https://helpingai.co/license)
|
29 |
+
|
30 |
+
## Training Data
|
31 |
+
|
32 |
+
HelpingAI3 was trained on a diverse dataset comprising:
|
33 |
+
|
34 |
+
- **Emotional Dialogues**: 15 million rows to enhance conversational intelligence.
|
35 |
+
- **Therapeutic Exchanges**: 3 million rows aimed at providing advanced emotional support.
|
36 |
+
- **Cultural Conversations**: 250,000 rows to improve global awareness.
|
37 |
+
- **Crisis Response Scenarios**: 1 million rows to better handle emergency situations.
|
38 |
+
|
39 |
+
## Training Procedure
|
40 |
+
|
41 |
+
The model underwent the following training processes:
|
42 |
+
|
43 |
+
- **Base Model**: Initiated from HelpingAI2.5.
|
44 |
+
- **Emotional Intelligence Training**: Employed Reinforcement Learning for Emotion Understanding (RLEU) and context-aware conversational fine-tuning.
|
45 |
+
- **Optimization**: Utilized mixed-precision training and advanced token efficiency techniques.
|
46 |
+
|
47 |
+
## Intended Use
|
48 |
+
|
49 |
+
HelpingAI3 is designed for:
|
50 |
+
|
51 |
+
- **AI Companionship & Emotional Support**: Offering empathetic interactions.
|
52 |
+
- **Therapy & Wellbeing Guidance**: Assisting in mental health support.
|
53 |
+
- **Personalized Learning**: Tailoring educational content to individual needs.
|
54 |
+
- **Professional AI Assistance**: Enhancing productivity in professional settings.
|
55 |
+
|
56 |
+
## Limitations
|
57 |
+
|
58 |
+
While HelpingAI3 strives for high emotional intelligence, users should be aware of potential limitations:
|
59 |
+
|
60 |
+
- **Biases**: The model may inadvertently reflect biases present in the training data.
|
61 |
+
- **Understanding Complex Emotions**: There might be challenges in accurately interpreting nuanced human emotions.
|
62 |
+
- **Not a Substitute for Professional Help**: For serious emotional or psychological issues, consulting a qualified professional is recommended.
|
63 |
+
|
64 |
+
## How to Use
|
65 |
+
|
66 |
+
### Using Transformers
|
67 |
+
|
68 |
+
```python
|
69 |
+
import torch
|
70 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
71 |
+
|
72 |
+
# Load the HelpingAI3 model
|
73 |
+
model = AutoModelForCausalLM.from_pretrained("HelpingAI/HelpingAI-3")
|
74 |
+
# Load the tokenizer
|
75 |
+
tokenizer = AutoTokenizer.from_pretrained("HelpingAI/HelpingAI-3")
|
76 |
+
|
77 |
+
# Define the chat input
|
78 |
+
chat = [
|
79 |
+
{"role": "system", "content": "You are HelpingAI, an emotional AI. Always answer my questions in the HelpingAI style."},
|
80 |
+
{"role": "user", "content": "Introduce yourself."}
|
81 |
+
]
|
82 |
+
|
83 |
+
inputs = tokenizer.apply_chat_template(
|
84 |
+
chat,
|
85 |
+
add_generation_prompt=True,
|
86 |
+
return_tensors="pt"
|
87 |
+
).to(model.device)
|
88 |
+
|
89 |
+
# Generate text
|
90 |
+
outputs = model.generate(
|
91 |
+
inputs,
|
92 |
+
max_new_tokens=256,
|
93 |
+
do_sample=True,
|
94 |
+
temperature=0.6,
|
95 |
+
top_p=0.9,
|
96 |
+
)
|
97 |
+
|
98 |
+
response = outputs[0][inputs.shape[-1]:]
|
99 |
+
print(tokenizer.decode(response, skip_special_tokens=True))
|
100 |
+
```
|