jpacifico commited on
Commit
62b2c50
1 Parent(s): c39e974

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +55 -178
README.md CHANGED
@@ -1,199 +1,76 @@
1
  ---
2
  library_name: transformers
3
- tags: []
 
 
 
 
 
 
 
 
 
4
  ---
5
 
6
- # Model Card for Model ID
7
 
8
- <!-- Provide a quick summary of what the model is/does. -->
9
 
10
-
11
-
12
- ## Model Details
13
 
14
  ### Model Description
15
 
16
- <!-- Provide a longer summary of what this model is. -->
17
-
18
- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
19
-
20
- - **Developed by:** [More Information Needed]
21
- - **Funded by [optional]:** [More Information Needed]
22
- - **Shared by [optional]:** [More Information Needed]
23
- - **Model type:** [More Information Needed]
24
- - **Language(s) (NLP):** [More Information Needed]
25
- - **License:** [More Information Needed]
26
- - **Finetuned from model [optional]:** [More Information Needed]
27
-
28
- ### Model Sources [optional]
29
-
30
- <!-- Provide the basic links for the model. -->
31
-
32
- - **Repository:** [More Information Needed]
33
- - **Paper [optional]:** [More Information Needed]
34
- - **Demo [optional]:** [More Information Needed]
35
-
36
- ## Uses
37
-
38
- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
-
40
- ### Direct Use
41
-
42
- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
-
44
- [More Information Needed]
45
-
46
- ### Downstream Use [optional]
47
-
48
- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
-
50
- [More Information Needed]
51
-
52
- ### Out-of-Scope Use
53
-
54
- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
-
56
- [More Information Needed]
57
-
58
- ## Bias, Risks, and Limitations
59
-
60
- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
-
62
- [More Information Needed]
63
-
64
- ### Recommendations
65
-
66
- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
-
68
- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
-
70
- ## How to Get Started with the Model
71
-
72
- Use the code below to get started with the model.
73
-
74
- [More Information Needed]
75
-
76
- ## Training Details
77
-
78
- ### Training Data
79
-
80
- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
-
82
- [More Information Needed]
83
-
84
- ### Training Procedure
85
-
86
- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
-
88
- #### Preprocessing [optional]
89
-
90
- [More Information Needed]
91
-
92
-
93
- #### Training Hyperparameters
94
-
95
- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
-
97
- #### Speeds, Sizes, Times [optional]
98
-
99
- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
-
101
- [More Information Needed]
102
-
103
- ## Evaluation
104
-
105
- <!-- This section describes the evaluation protocols and provides the results. -->
106
-
107
- ### Testing Data, Factors & Metrics
108
-
109
- #### Testing Data
110
-
111
- <!-- This should link to a Dataset Card if possible. -->
112
-
113
- [More Information Needed]
114
-
115
- #### Factors
116
-
117
- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
-
119
- [More Information Needed]
120
-
121
- #### Metrics
122
-
123
- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
-
125
- [More Information Needed]
126
-
127
- ### Results
128
-
129
- [More Information Needed]
130
-
131
- #### Summary
132
-
133
-
134
-
135
- ## Model Examination [optional]
136
-
137
- <!-- Relevant interpretability work for the model goes here -->
138
-
139
- [More Information Needed]
140
-
141
- ## Environmental Impact
142
-
143
- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
-
145
- Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
-
147
- - **Hardware Type:** [More Information Needed]
148
- - **Hours used:** [More Information Needed]
149
- - **Cloud Provider:** [More Information Needed]
150
- - **Compute Region:** [More Information Needed]
151
- - **Carbon Emitted:** [More Information Needed]
152
-
153
- ## Technical Specifications [optional]
154
-
155
- ### Model Architecture and Objective
156
-
157
- [More Information Needed]
158
-
159
- ### Compute Infrastructure
160
-
161
- [More Information Needed]
162
-
163
- #### Hardware
164
-
165
- [More Information Needed]
166
-
167
- #### Software
168
-
169
- [More Information Needed]
170
-
171
- ## Citation [optional]
172
-
173
- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
-
175
- **BibTeX:**
176
 
177
- [More Information Needed]
178
 
179
- **APA:**
180
 
181
- [More Information Needed]
182
 
183
- ## Glossary [optional]
184
 
185
- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
 
 
 
 
 
 
 
 
 
 
 
 
186
 
187
- [More Information Needed]
 
 
 
 
 
 
 
188
 
189
- ## More Information [optional]
 
 
 
190
 
191
- [More Information Needed]
192
 
193
- ## Model Card Authors [optional]
 
 
 
194
 
195
- [More Information Needed]
196
 
197
- ## Model Card Contact
 
198
 
199
- [More Information Needed]
 
 
 
 
1
  ---
2
  library_name: transformers
3
+ license: mit
4
+ language:
5
+ - fr
6
+ - en
7
+ datasets:
8
+ - jpacifico/French-Alpaca-dataset-Instruct-110K
9
+ tags:
10
+ - Phi-3
11
+ - french
12
+ - Phi-3-mini
13
  ---
14
 
15
+ ## Model Card for Model ID
16
 
17
+ French-Alpaca based microsoft/Phi-3-mini-128k-instruct
18
 
19
+ ![image/jpeg](https://github.com/jpacifico/French-Alpaca/blob/main/Assets/French-Alpaca_500px.png?raw=true)
 
 
20
 
21
  ### Model Description
22
 
23
+ fine-tuned from the original French-Alpaca-dataset entirely generated with OpenAI GPT-3.5-turbo.
24
+ French-Alpaca is a general model and can itself be finetuned to be specialized for specific use cases.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
25
 
26
+ The fine-tuning method is inspired from https://crfm.stanford.edu/2023/03/13/alpaca.html
27
 
28
+ Quantized GGUF version : coming soon
29
 
 
30
 
31
+ ### Usage
32
 
33
+ ```python
34
+ def stream_response(instruction, max_new_tokens=500, temperature=0.0, do_sample=False):
35
+ messages = [
36
+ {"role": "system", "content": "Vous êtes un assistant numérique serviable. Veuillez fournir des informations sûres, éthiques et précises à l'utilisateur."},
37
+ {"role": "user", "content": instruction}
38
+ ]
39
+
40
+ conversation_history = ""
41
+ for msg in messages:
42
+ conversation_history += msg["role"] + ": " + msg["content"] + "\n"
43
+
44
+ inputs = tokenizer(conversation_history, return_tensors="pt", padding=True, truncation=True)
45
+ input_ids = inputs['input_ids'].to("cuda")
46
 
47
+ output_sequences = model.generate(
48
+ input_ids=input_ids,
49
+ max_length=input_ids.shape[1] + max_new_tokens,
50
+ temperature=temperature,
51
+ do_sample=do_sample,
52
+ pad_token_id=tokenizer.eos_token_id,
53
+ eos_token_id=None
54
+ )
55
 
56
+ generated_text = tokenizer.decode(output_sequences[0], skip_special_tokens=True)
57
+ last_user_message = "user: " + instruction
58
+ response_start_index = generated_text.rfind(last_user_message) + len(last_user_message)
59
+ response = generated_text[response_start_index:].strip()
60
 
61
+ print(response)
62
 
63
+ # Exemple d'utilisation
64
+ instruction = "propose moi des façons de combiner des bananes et des pitayas pour les consommer."
65
+ stream_response(instruction)
66
+ ```
67
 
68
+ ### Limitations
69
 
70
+ The French-Alpaca model is a quick demonstration that a base tiny model can be easily fine-tuned to specialize in a particular language.
71
+ It does not have any moderation mechanisms.
72
 
73
+ - **Developed by:** Jonathan Pacifico, 2024
74
+ - **Model type:** LLM
75
+ - **Language(s) (NLP):** French
76
+ - **License:** MIT